Whether you are sizing up a college, comparing graduate programs, analyzing a hiring funnel, or tracking a scholarship's competitiveness, one number cuts through the noise faster than any ranking list or brochure: the acceptance rate. A single percentage tells you exactly how selective a process is. An acceptance rate calculator gets you that number in seconds — enter how many people applied and how many were accepted, and the result appears instantly.This guide explains the formula, what the numbers mean across every context where acceptance rates matter, how to interpret results for colleges, jobs, grants, and programs, and where people consistently misread or misuse the statistic. Whether you are a high school student building a college list, an HR analyst reviewing a hiring pipeline, or an admissions officer checking year-over-year trends, the calculation is always the same.

What Is an Acceptance Rate Calculator and Why Does It Matter

An acceptance rate calculator determines the percentage of applicants who received an offer of admission or acceptance from a program, institution, or employer by dividing the number of accepted applicants by the total number of applicants and multiplying by 100. Students, parents, college counselors, HR professionals, grant writers, program administrators, and researchers all use it to measure and compare selectivity across different opportunities. The core formula is: Acceptance Rate (%) equals (Accepted Applicants divided by Total Applicants) multiplied by 100. Getting this number right matters because acceptance rate is the single most widely cited measure of competitiveness — a 5% acceptance rate at a university tells a prospective applicant more about their realistic odds than any ranking or prestige label, and an 80% offer rate on a job posting tells a recruiter something is wrong with candidate sourcing long before the next hiring cycle begins.

What You Need Before You Start

Have the following ready before using the acceptance rate calculator:

- Total number of applicants — every person who submitted a complete application in the period you are analyzing. Do not include inquiries, partial applications, or withdrawn submissions that were never formally reviewed.

- Number of accepted applicants — everyone who received a formal offer of acceptance, admission, or approval. This figure should not include waitlisted applicants, conditional admits pending additional requirements, or deferred candidates unless they were ultimately offered a place.

- The time period or cohort — acceptance rates shift year over year for competitive programs, so specify whether you are calculating for a single cycle, a semester, or an annual period.

- Whether you want yield rate as well — yield rate (the percentage of accepted applicants who actually enroll) is a separate but related metric that requires the number of matriculating students as an additional input.

- Any segment breakdowns if analyzing subgroups — many institutions track acceptance rates separately by demographic group, major, residency status, or application round. Each subgroup needs its own applicant and accepted count.

How to Use This Acceptance Rate Calculator Step by Step

Enter your numbers in order for an instant result and category classification.

1. Enter the total number of applicants — the complete pool of people who formally applied during your selected period.

2. Enter the number of accepted applicants — everyone who received a formal acceptance offer from that same pool.

3. Click Calculate. The result shows acceptance rate as a percentage, rejection rate (the complement), the number of rejected applicants, selectivity category, and a plain-English interpretation of what your result means.

4. Optionally enter the number who enrolled for a yield rate calculation — yield equals enrolled students divided by accepted students, multiplied by 100.

5. If comparing two periods or programs, enter a second set of numbers to see the percentage point change in acceptance rate and the direction of the trend.

6. Review the selectivity category label — the calculator classifies results as open access, minimally selective, selective, highly selective, or most selective based on widely used educational benchmarks.

7. Note the rejection count and rate alongside the acceptance rate — both numbers together tell a more complete story than either alone.

The Acceptance Rate Calculator Formula Explained Simply

Acceptance rate is a ratio — the fraction of applicants who got in, expressed as a percentage. It is one of the simplest calculations in statistics, which is partly why it is so widely used and so frequently misunderstood. The formula has no variables beyond the two counts you enter, and it applies identically whether you are measuring college admissions, medical school interviews, job offers, grant awards, or visa approvals.

Core Formula:

Acceptance Rate (%) = (Accepted Applicants / Total Applicants) x 100

Rejection Rate:

Rejection Rate (%) = 100 - Acceptance Rate

Or equivalently:

Rejection Rate (%) = ((Total Applicants - Accepted Applicants) / Total Applicants) x 100

Yield Rate (separate metric):

Yield Rate (%) = (Enrolled Students / Accepted Students) x 100

Year-over-Year Change:

Change (percentage points) = Current Year Rate - Prior Year Rate

- Total Applicants: the denominator — everyone who formally applied. Realistic range for a large university: 20,000 to 100,000+ applications per year. Realistic range for a small selective college: 5,000 to 20,000.

- Accepted Applicants: the numerator — everyone who received an unconditional or conditional offer. For the most selective US universities, this figure ranges from 3% to 15% of applicants. For open-enrollment community colleges, it may approach 100%.

- Acceptance Rate Result: a percentage between 0% and 100%. Lower numbers indicate higher selectivity. The result is always rounded to one or two decimal places for reporting.

The formula works because it expresses a conditional probability in accessible percentage form. An acceptance rate of 8% means that if you were a randomly selected applicant from that pool, your chance of receiving an offer — without knowing anything about your qualifications — would be 8 in 100. Of course, individual chances vary enormously within the pool based on qualifications, so the institutional rate is a population statistic, not a personal prediction.

This formula is the standard used by the National Center for Education Statistics (NCES) in the Integrated Postsecondary Education Data System (IPEDS), the Common Data Set (CDS) used by most US colleges, and the US News and World Report college rankings methodology. It is also the standard metric for selectivity in employment, grant-making, and program selection contexts.

Acceptance Rate Calculator Worked Examples

Eaxmple1:Calculating a University's Acceptance Rate — High School Senior Research

A high school senior researching colleges finds that a state university received 48,200 applications for its most recent incoming class and admitted 14,460 students. She wants to know the acceptance rate and how it compares to the previous year's rate of 32.4%.

1. Total applicants: 48,200

2. Accepted applicants: 14,460

3. Acceptance rate: (14,460 / 48,200) x 100 = 29.99% — rounded to 30.0%

4. Rejection rate: 100 - 30.0 = 70.0%

5. Rejected applicants: 48,200 - 14,460 = 33,740 students rejected

6. Year-over-year change: 30.0% - 32.4% = -2.4 percentage points (becoming more selective)

7. Selectivity category: Selective (20% to 40% acceptance range)

The acceptance rate dropped 2.4 percentage points in a single year — a meaningful shift for a large public university. This pattern is common when application volume grows faster than enrollment capacity. She notes that 30% acceptance sounds reasonably accessible, but she should also check her GPA and test score against the admitted student profile in the school's Common Data Set rather than relying on the overall rate, which includes both strong and weak applicants.

Example2:Medical School Application — Highly Selective Program

A pre-med student is evaluating a medical school that received 6,800 applications and sent acceptance letters to 119 students for an entering class of 95 (some accepted students chose other schools).

1. Total applicants: 6,800

2. Accepted applicants: 119

3. Acceptance rate: (119 / 6,800) x 100 = 1.75%

4. Rejection rate: 100 - 1.75 = 98.25%

5. Rejected applicants: 6,800 - 119 = 6,681 students not offered a place

6. Yield rate: (95 / 119) x 100 = 79.8% of accepted students enrolled

7. Selectivity category: Most Selective (under 5%)

At 1.75%, this medical school is more selective than Harvard's undergraduate program. The 79.8% yield rate tells an additional story — nearly 4 in 5 accepted students chose to enroll, signaling that the school is a top choice for most of the small group who receive offers, not a safety school that gets rejected by its own admitted students. For a pre-med student, knowing both the acceptance rate and the yield rate helps calibrate how many schools to apply to and which tier to target.

Example3:Corporate Hiring Funnel — HR Analyst Perspective

An HR analyst at a mid-size technology company is reviewing the hiring pipeline for a software engineering role. The posting received 1,240 applications and 31 offers were extended. She wants to know the offer rate and benchmark it against industry norms.

1. Total applicants: 1,240

2. Accepted (offer extended): 31

3. Offer rate: (31 / 1,240) x 100 = 2.5%

4. Rejection rate: 100 - 2.5 = 97.5%

5. Rejected applicants: 1,240 - 31 = 1,209 candidates not offered the role

6. Industry benchmark for software engineering roles at mid-size tech firms: typical offer rates run 1% to 5% for specialized roles with strong applicant pools

7. Assessment: 2.5% is within the normal range — but she flags that if only 18 of the 31 offers were accepted, the effective yield is 58%, suggesting some candidates received better offers elsewhere

For an HR analyst, acceptance rates and yield rates together define the health of a hiring funnel. A very low offer rate combined with a low yield suggests the compensation package or role is not competitive. A normal offer rate with a high yield (above 70%) indicates a well-calibrated process. Tracking these numbers quarter over quarter reveals trends before they become staffing emergencies.

Example4:Grant and Scholarship Program — Edge Case with Multiple Rounds

A foundation awards scholarships through a two-stage process. Stage 1 reviewed 3,200 complete applications and passed 480 to Stage 2. Stage 2 reviewed those 480 and awarded scholarships to 64 finalists. The foundation wants to report overall acceptance rate and stage-by-stage rates.

1. Stage 1 acceptance rate: (480 / 3,200) x 100 = 15.0%

2. Stage 2 acceptance rate: (64 / 480) x 100 = 13.3%

3. Overall acceptance rate (final awards from total applicants): (64 / 3,200) x 100 = 2.0%

4. Rejection rate overall: 100 - 2.0 = 98.0%

5. Cumulative probability of receiving an award: 15% x 13.3% = 2.0% — confirms the direct calculation

The overall rate of 2.0% gives an accurate picture for applicants who want to know their odds of winning a scholarship. The stage-by-stage rates tell the program administrators where attrition occurs — 15% pass Stage 1, and then nearly the same fraction (13.3%) of those advance to a final award. An unusually high or low Stage 2 rate compared to Stage 1 would suggest calibration issues in one of the review rounds.

Acceptance Rate Calculator Results What the Numbers Mean

The acceptance rate result is a selectivity benchmark. What counts as high or low depends entirely on the context — a 30% acceptance rate at a top law school is highly selective, while a 30% acceptance rate at a mid-size staffing agency for a customer service role might signal their screening is too loose.For college and university admissions, the most widely used classification framework comes from published data in the Common Data Set and NCES IPEDS reporting:

Acceptance Rate | Selectivity Category | Example Institutions (2025-2026)

Under 5% | Most Selective | Harvard (3.6%), Stanford (3.7%), MIT (4%)

5% to 15% | Highly Selective | UCLA (9%), Georgetown (13%), Emory (13%)

15% to 25% | Very Selective | University of Michigan (18%), NYU (21%)

25% to 40% | Selective | Indiana University (34%), Miami (37%)

40% to 65% | Moderately Selective | Most state flagship universities

65% to 80% | Minimally Selective | Many regional universities

Above 80% | Open Access or Near-Open | Community colleges, many state schools

For non-academic contexts, acceptance rate benchmarks shift significantly:

Context | Typical Acceptance Rate | Notes

Software engineering jobs | 1% to 5% | High applicant volume for specialized roles

Medical school (MD) | 2% to 6% | Average US MD school: approximately 5.5%

Law school (top 14) | 8% to 25% | Varies widely by school

Venture capital funding | 1% to 3% | Of startups that pitch, not of all inquiries

Academic journal papers | 5% to 30% | Varies by journal prestige and field

NSF research grants | 20% to 30% | Federal science grants

Fulbright Scholarship | Approximately 20% | Varies by country and program

The most common misunderstanding is treating the institutional acceptance rate as a personal probability. A 10% acceptance rate does not mean every applicant has a 10% chance of getting in. It means that 10% of the applicants — who range from extremely well-qualified to very unlikely candidates — received offers. A well-qualified applicant at a 10% school may have a 40% personal chance. A poorly matched applicant at a 40% school may have nearly no chance. The overall rate is a population average, not an individual forecast.

How Your Inputs Change the Result

Total applicant volume is the input that most dramatically shifts acceptance rates at institutions with fixed class sizes. When a university admits a fixed number of students each year and application volume increases, the acceptance rate falls automatically — even if the school's standards haven't changed. This is why acceptance rates at elite universities have dropped steadily over the past 20 years: class sizes have grown modestly while application pools have expanded dramatically because of the Common App making multi-school applications easier.

Total Apps | Fixed Admits | Acceptance Rate | Year-over-Year Change

20,000 | 2,000 | 10.0% | Baseline

25,000 | 2,000 | 8.0% | -2.0 pp (more competitive)

30,000 | 2,000 | 6.7% | -3.3 pp from baseline

40,000 | 2,000 | 5.0% | -5.0 pp from baseline

50,000 | 2,100 | 4.2% | Class grew by 100, still fell

The number of accepted students controls the numerator. Expanding a class by just 50 students at a school receiving 20,000 applications moves the acceptance rate from 10.0% to 10.25% — essentially invisible. Cutting admits by 100 moves it from 10.0% to 9.5% — a 0.5 percentage point drop that can appear significant in press coverage even though the practical difference for applicants is minimal. Small changes in admits at high-volume schools move the rate more slowly than most people expect.

Subgroup analysis produces very different rates within the same overall figure. A university with a 12% overall acceptance rate may admit 25% of in-state applicants and only 8% of out-of-state applicants. It may admit 60% of recruited athletes and 6% of the general applicant pool. Early decision acceptance rates at selective schools routinely run two to three times higher than regular decision rates at the same institution. The overall rate hides all of this variation, which is why breaking the calculation into meaningful subgroups provides far more useful information for applicants.

Year-over-year tracking reveals trends that a single data point cannot. A school whose acceptance rate falls from 35% to 28% over five years is becoming meaningfully more competitive even if the current 28% sounds accessible. A school whose rate rises from 22% to 30% over the same period may be struggling with enrollment and may be more accessible — or more generous with financial aid — than its historical reputation suggests.

Acceptance Rate Calculator Common Mistakes to Avoid

- Including waitlisted students in the accepted count. Waitlisted applicants have not been admitted — they are in a separate pool that may or may not result in an offer depending on yield from the admitted class. Including them inflates the apparent acceptance rate. Only count students who received a formal, unconditional (or conditionally unconditional) offer of admission.

- Confusing acceptance rate with enrollment rate or yield rate. Acceptance rate measures who gets an offer. Yield rate measures who accepts the offer and enrolls. A school with a 15% acceptance rate and a 40% yield is a very different institution from one with a 15% acceptance rate and a 90% yield. Both have the same acceptance rate but very different enrollment dynamics and campus demographics.

- Using acceptance rate as a direct proxy for your personal odds. The institutional rate is a population average across a hugely diverse pool. Applicants with GPAs, test scores, and profiles well above the median admitted student have meaningfully better odds than the overall rate suggests. Applicants well below the median have meaningfully worse odds. Use acceptance rate to gauge general competitiveness, then check your specific metrics against the school's Common Data Set for a calibrated picture.

- Comparing acceptance rates across different contexts without adjustment. A 20% acceptance rate for a federal research grant is a very different signal from a 20% acceptance rate at a large state university. A 5% job offer rate at a big four consulting firm is highly competitive in recruiting terms; a 5% grant approval rate at a small local foundation might indicate inadequate program funding. Always compare acceptance rates within the same context category.

- Calculating acceptance rate from a non-representative applicant pool. Some programs only count completed applications in their denominator. Others count all inquiries, started applications, or registered test takers. If the denominator definition differs across institutions, the resulting rates are not directly comparable even within the same category. Always check whether an institution's reported rate uses complete applications or a broader definition.

- Treating a rising acceptance rate as automatically good for applicants. A rising acceptance rate can mean more spots are available — or it can mean application volume has dropped, suggesting the institution is losing prestige, facing enrollment pressure, or struggling to attract applicants. Context determines whether a higher rate is a positive development. For applicants, a rising rate at a school you want to attend may represent an opportunity. For the institution, it may represent a challenge.

- Not accounting for Early Decision versus Regular Decision differences. At many selective universities, Early Decision (ED) acceptance rates run 20 to 30 percentage points higher than Regular Decision rates. A student who sees a 12% overall acceptance rate and applies Regular Decision without knowing the ED split is making decisions with incomplete information. The overall rate averages a more accessible ED pool with a far more competitive RD pool.

- Using the acceptance rate from the wrong year. Acceptance rates shift meaningfully from year to year, especially at institutions with rising application volumes. A rate published in 2022 for a highly competitive school may be 3 to 5 percentage points different from the current figure. Always use the most recent Common Data Set or IPEDS filing for current planning purposes.

Key Terms Explained

Acceptance Rate

The percentage of applicants who receive a formal offer of admission or selection from a program, institution, or employer — calculated as accepted applicants divided by total applicants, multiplied by 100.

Yield Rate

The percentage of accepted applicants who ultimately enroll or accept the offer — calculated as enrolled students divided by accepted students, multiplied by 100. Different from acceptance rate; an institution can have a low acceptance rate and a low yield rate if many admitted students choose to go elsewhere.

Common Data Set (CDS)

A standardized set of data items published annually by most US colleges and universities, used by rankings organizations and admissions reference services. Section C of the CDS contains official application and admission counts that are the most reliable source for acceptance rate calculations.

IPEDS

The Integrated Postsecondary Education Data System, maintained by the National Center for Education Statistics (NCES). IPEDS collects and publishes admissions data — including application counts, admission counts, and enrollment figures — for all accredited US postsecondary institutions. Available free at nces.ed.gov/ipeds.

Selectivity

A qualitative classification of how competitive an admissions or selection process is, typically derived from acceptance rate benchmarks. Ranges from open access (virtually all applicants admitted) through most selective (under 5% admitted).

Early Decision (ED)

A binding application round offered by many US colleges in which students apply early (typically November) and commit to enrolling if admitted. ED acceptance rates are significantly higher than regular decision rates at many selective schools because ED applicants demonstrate demonstrated interest and the school can better predict yield.

Denominator Definition

The specific count used as the total applicant figure in the acceptance rate formula. Institutions may count all individuals who started an application, only those who submitted a complete application, or only those whose applications were reviewed. Different denominator definitions make rates at different institutions non-comparable even within the same selectivity tier.

Rejection Rate

The complement of acceptance rate — the percentage of applicants who did not receive an offer. Rejection Rate equals 100 minus Acceptance Rate. A 12% acceptance rate implies an 88% rejection rate. Both numbers always add to exactly 100%.

How This Calculator Works Methodology

This acceptance rate calculator applies the formula: Acceptance Rate (%) equals (Accepted Applicants divided by Total Applicants) multiplied by 100. This is the standard formula used by the National Center for Education Statistics in IPEDS data collection (nces.ed.gov/ipeds) and the Common Data Set Initiative, a collaboration between the College Board, Peterson's, and US News and World Report, as described in the CDS definitions document (commondataset.org).

Rejection rate is calculated as 100 minus the acceptance rate. Rejected applicants are calculated as Total Applicants minus Accepted Applicants. Yield rate (when enrollment count is entered) is calculated as Enrolled divided by Accepted, multiplied by 100. Year-over-year change is calculated as Current Rate minus Prior Rate, expressed in percentage points.

Selectivity categories follow the classifications used in published higher education research and admissions counseling practice: Most Selective (under 5%), Highly Selective (5% to 15%), Very Selective (15% to 25%), Selective (25% to 40%), Moderately Selective (40% to 65%), Minimally Selective (65% to 80%), Open Access (above 80%). These thresholds are consistent with classifications used in the Barron's Profiles of American Colleges selectivity index.

All results are rounded to two decimal places. The calculator does not model individual admission probability — it calculates population-level statistics only. No demographic weighting, recalibration for subgroup rates, or predictive modeling is applied.

Frequently Asked Questions About Acceptance Rate Calculator

1. What is the acceptance rate and how is it calculated?

Acceptance rate is the percentage of applicants who receive an offer of admission, a job, a scholarship, or any form of selection from a given pool. The formula is: Acceptance Rate equals Accepted Applicants divided by Total Applicants, multiplied by 100. For example, if a college received 40,000 applications and admitted 4,800 students, the acceptance rate is (4,800 / 40,000) x 100 = 12%. It applies to any process where people apply and decisions are made about who gets in.

2. How accurate is an acceptance rate calculator?

The calculation itself is mathematically exact — there is no approximation or rounding in dividing accepted by total and multiplying by 100. The accuracy of the result depends entirely on the accuracy of the two input numbers. Official figures from IPEDS, the Common Data Set, or directly from an institution's admissions office are the most reliable. Self-reported or media-reported figures may differ slightly from official submissions.

3. What is the formula for acceptance rate?

Acceptance Rate (%) equals (Number of Accepted Applicants divided by Total Number of Applicants) multiplied by 100. The rejection rate is the complement: 100 minus the acceptance rate. Both always sum to exactly 100%. Yield rate is a separate calculation: (Number Who Enrolled divided by Number Accepted) multiplied by 100.

4. Is a 50% acceptance rate good or bad for a college?

A 50% acceptance rate places a college in the moderately accessible range for undergraduate admissions. It is not highly selective, but it does not mean anyone who applies gets in. For most state universities and many mid-tier private colleges, a 50% rate is typical and reflects a genuine review process. Whether it is good or bad depends on what the applicant is looking for — academic fit, financial aid, location, and program quality matter far more than a selectivity percentage.

5. When should an acceptance rate calculator not be used?

An acceptance rate calculator gives a population-level statistic that does not predict individual outcomes. It should not be used as a direct forecast of whether any specific person will be admitted. It also does not apply when comparing programs that use different denominator definitions — some schools count complete applications, others count all registered applicants or test takers. When definitions differ, the rates are not directly comparable even if the numbers look similar.

6. How do I get the most accurate acceptance rate for a school?

The most accurate source for a US college or university's acceptance rate is its Common Data Set (CDS), which institutions submit annually. Search the school's name and "Common Data Set" to find the PDF — Section C1 contains the official application and admission counts. IPEDS (nces.ed.gov/ipeds) also publishes verified institutional data for all accredited US postsecondary institutions. Both sources are more reliable than rankings websites, which may use older data or different counting methods.

7. What is a typical acceptance rate for US colleges?

The range is enormous. The most selective research universities admit under 5% of applicants. Most selective liberal arts colleges admit 10% to 25%. Regional universities and many state schools admit 40% to 70%. Open-enrollment community colleges admit virtually all applicants, producing rates above 90%. The average acceptance rate across all degree-granting institutions in the US, weighted by application volume, is substantially higher than the rates of elite schools that dominate media coverage.

8. Should I consult a college counselor to interpret my acceptance chances?

Yes, for high-stakes decisions. An acceptance rate tells you how selective a school is for its entire applicant pool. A college counselor who can review your specific GPA, test scores, extracurriculars, geographic background, and intended major can give you a far more accurate personal probability estimate than any population-level acceptance rate. Independent Educational Consultants Association (IECA) certified counselors and school-based counselors both provide this service.

Related Calculators Worth Bookmarking

- GPA Calculator — calculates your weighted and unweighted GPA from course grades and credit hours, providing the academic metric most directly relevant to your individual admissions prospects alongside any school's acceptance rate.

- SAT Score Percentile Calculator — converts your SAT composite and section scores into percentile rankings, helping you understand how your scores compare to the admitted student profile at schools you are researching.

- Scholarship Odds Calculator — estimates your competitiveness for merit and need-based scholarships using GPA, test scores, and financial information, a natural companion to acceptance rate research for full cost planning.

- College Cost Calculator — estimates your net price at any institution after grants and scholarships, using institutional net price data from IPEDS, which pairs with acceptance rate data from the same source.

- Hiring Funnel Conversion Calculator — tracks application-to-offer and offer-to-accept conversion rates at each stage of a hiring pipeline, extending acceptance rate analysis into full recruitment funnel metrics for HR use.

- Statistical Significance Calculator — tests whether the difference between two acceptance rates from different years or programs is statistically meaningful or likely due to random variation in small samples.

- Survey Response Rate Calculator — calculates the percentage of distributed surveys that were returned with complete responses, applying the same accepted-over-total formula to research data collection instead of admissions.

- Grant Success Rate Tracker — monitors acceptance rates across multiple grant applications over time, helping researchers and nonprofits identify which funders and program types yield the best return on proposal effort.

References and Further Reading

1. National Center for Education Statistics. Integrated Postsecondary Education Data System (IPEDS) Glossary and Data Collection. NCES, US Department of Education, 2026. nces.ed.govipeds.

2. Common Data Set Initiative. Common Data Set Definitions and Instructions. College Board, Peterson's, US News and World Report, 2025-2026. commondataset.org.

3. Barron's Educational Series. Barron's Profiles of American Colleges. Barron's, 2026 edition.

4. Association of American Medical Colleges. AAMC Facts and Figures: Medical School Applicants, Matriculants, Enrollment. AAMC, 2025. aamc.org.

5. RemNote Educational Research. College Acceptance Rate: Definition, Formula and Rankings. RemNote, April 2026.

Important Disclaimer

This acceptance rate calculator is provided for informational and educational purposes only. Results reflect population-level statistics calculated from the numbers you enter and do not predict any individual applicant's probability of admission, selection, or acceptance. Acceptance rates vary by applicant pool, application round, subgroup, and year. Institutional acceptance rates published in this article are sourced from publicly available data as of 2025 to 2026 and may change with each new admissions cycle. This tool does not constitute college counseling, career counseling, or professional admissions advice. Consult a certified college counselor, licensed career professional, or the admissions office of your target institution for personalized guidance.