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Last updated: June 4, 2026

Law School Admissions Calculator

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Law School Admissions Calculator: How to Use It Well

Goal: estimate the likelihood of admission based on LSAT, GPA, and school selectivity, with an optional application-strength boost. This tool gives an educational approximation to help you plan targets and strategy—not an official decision predictor.

Inputs

  • LSAT score (120–180)
  • Undergrad GPA (0.0–4.0)
  • School selectivity (tier): T14, Selective, or Regional
  • Application strength boost (−0.10 to +0.30 typical). Use 0 if unsure.

Outputs

  • Index score (unitless)
  • Estimated admit probability (0–100%)

Assumptions

  • Logistic model using LSAT and GPA, with tier-specific weights and a shift.
  • Boost adjusts the log-odds (index), representing soft factors (e.g., compelling work history, extraordinary leadership, URM, strong recommendations). It is not a guarantee.
  • Applies to first-degree U.S. JD programs; rounding and tier anchoring simplify variation across schools.

Method (kept simple)

We compute a tier-specific index, then convert it to a probability using a logistic function. Constants differ by tier.

  • Index (T14): index_t14 = a_t14 · LSAT + b_t14 · GPA + c_t14 + shift_t14
  • Index (Selective): index_selective = a_selective · LSAT + b_selective · GPA + c_selective + shift_selective
  • Index (Regional): index_regional = a_regional · LSAT + b_regional · GPA + c_regional + shift_regional
  • Choose index by selected tier.
  • Probability: probability = 1 / (1 + exp(−(index + boost)))

Parameters (by tier)

  • T14: a=0.07, b=0.90, c=−12.0, shift=−1.2
  • Selective: a=0.065, b=0.85, c=−10.0, shift=0.0
  • Regional: a=0.06, b=0.80, c=−8.0, shift=+1.0

Worked Examples

  • Example A (T14 stretch): LSAT=170, GPA=3.9, Tier=T14, Boost=0.03. Index ≈ 1.03 → Probability ≈ 73.7%.
  • Example B (Selective match): LSAT=160, GPA=3.5, Tier=Selective, Boost=0. Index ≈ −0.65 → Probability ≈ 34.3%.

How to Interpret

  • 70–85%: solid odds; keep quality control on personal statements and timing.
  • 40–60%: competitive; nudge LSAT a bit or expand school list.
  • Under 30%: reach; consider retake planning and application-strength improvements.

Planning Tips

  • Target setting: move one input at a time to see sensitivity. For instance, +2 LSAT points in T14 ranges often shifts probability more than +0.05 GPA.
  • Boost calibration: if you have exceptional softs or a recognized boost (e.g., URM), try +0.15 to +0.30; for strong but not extraordinary experiences, +0.05 to +0.10; otherwise 0.
  • Tiers portfolio: run the calculator across T14, Selective, and Regional to form a balanced list (reaches, targets, likelies).

Validation and Edge Cases

  • Ranges: LSAT is clamped to 120–180; GPA to 0.0–4.0.
  • Do not mix GPAs (unweighted vs. school-reported). Use the official/standard 4.0 scale if available.
  • Early Decision is not explicitly modeled. A small positive boost may approximate its marginal effect, but policies vary.
  • International transcripts and grade conversions can shift real-world outcomes more than this model captures.

Quick Next Steps

  • If your probability is below your comfort level, test a new LSAT goal and map study weeks needed.
  • Create a short log: actual LSAT practice scores, GPA finalization, and any soft-factor milestones. Update your boost assumption conservatively.

Frequently Asked Questions

What does the index score represent?

It is a tier-anchored linear combination of LSAT and GPA. Higher index implies higher estimated log-odds of admission.

How should I set the boost value?

Use 0 by default; +0.05 to +0.10 for strong softs; +0.15 to +0.30 for exceptional profiles or recognized boosts. Keep it conservative.

Does this replace school-specific medians and 509 data?

No. Use it alongside each school’s LSAT/GPA ranges and recent admit profiles for a complete picture.

Can Early Decision be modeled here?

Not directly. You may simulate a small positive boost, but ED effects vary widely by school and year.

My GPA is not on a 4.0 scale. What do I do?

Convert to a 4.0 equivalent if possible (e.g., LSAC conversions). Avoid mixing unconverted values.

Why do probabilities change so much near the middle?

Logistic curves are steep around index ≈ 0. Small changes in LSAT or GPA can move probability noticeably in that region.

Is the tool accurate for all applicants?

It is an educational approximation. Unique experiences, institutional priorities, and year-to-year shifts can lead to different outcomes.

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