Justice Isn’t Blind: The Impact of Lawyer Appearance on Judicial Decision Making

Key Takeaways

Perceived lawyer attractiveness has a statistically significant, outcome-relevant impact on federal appellate decisions; The attractiveness effect persists after controlling for education, experience, ideology, and client resources; Multiple attractiveness measures (survey, video stills, machine learning, and relative ratings) converge on the same pattern; The influence of appearance seems especially pronounced in close or complex cases where legal guidance is weaker; Judicial decision making incorporates extra-legal heuristics, challenging the ideal of fully “blind” justice.

Dataset Description

The study examines all lawyers who delivered oral argument in the U.S. Courts of Appeals from 2017 to 2019 in cases against the U.S. government, yielding a dataset of more than 1,000 cases and over 3,000 individual judicial votes. Professional headshots from lawyers’ firms or professional websites were standardized (size, color, background) and rated for attractiveness by survey respondents on a numerical scale. Attractiveness scores were also generated by a supervised machine learning algorithm trained on facial features, and by a second survey based on still images drawn from courtroom video, along with a relative-attractiveness measure comparing each lawyer with opposing counsel. These attractiveness measures were merged with case outcomes and individual judge votes, alongside controls for law school attended, clerkship and professional background, client type (government versus private), judicial ideology, years of practice, prior argument experience, and resource indicators such as firm size.

Key Findings

Across more than 3,000 federal appellate judicial votes, lawyers who were rated as more physically attractive were systematically more likely to win, both in terms of individual judges’ votes and overall case outcomes against the U.S. government. Conditional on case characteristics, lawyer credentials, and judicial ideology, moving from mid-level to high attractiveness increased the predicted probability of a favorable outcome from roughly 31% to nearly 49%, corresponding to about a 6 percentage-point gain in win probability for every two-point increase on a nine-point attractiveness scale. The effect remained robust when attractiveness was remeasured using a machine-learning model trained on facial images, a second survey based on courtroom video stills, and a relative attractiveness metric that compared each lawyer to their opposing counsel. The attractiveness premium appeared strongest in closer or more complex cases, suggesting that time-pressured appellate judges rely on appearance as a heuristic for perceived competence, credibility, and even ideological proximity when legal signals are noisy. Overall, the study concludes that judicial decision-making at the appellate level is not fully insulated from extra-legal cues and that these cues can be large enough to alter the outcome of a non-trivial share of cases.

Summary

This piece synthesizes a recent empirical study examining whether federal appellate judges are influenced by the physical appearance of the lawyers who appear before them. Focusing on cases in which the U.S. government was a party in the U.S. Courts of Appeals between 2017 and 2019, the research builds a comprehensive dataset that links lawyers’ observable characteristics to individual judicial votes and case outcomes. The central question is whether perceived attractiveness, an arguably irrelevant trait, shapes how judges allocate their votes when evaluating legal arguments that should, in principle, be decided solely on the merits.

To operationalize attractiveness, the authors collect professional headshots for all lawyers who argued these appeals and standardize the images to minimize differences in lighting, background, and size. Independent survey respondents rate these photos on an attractiveness scale, generating a primary measure of perceived appearance. The study then adds additional measures: an algorithmic attractiveness score produced by a machine-learning model that analyzes facial features, and a second wave of human ratings based on still frames from actual courtroom video. A relative attractiveness index, comparing each advocate’s score to that of opposing counsel, adds a more competitive dimension to the analysis.

These attractiveness measures are combined with more than 3,000 judicial votes across over 1,000 cases, along with rich controls for lawyer pedigree (law school rank, prior clerkships), professional background (public service vs. private practice), client type and resources, and judge-level factors such as ideology and tenure. Regression models estimate how much of the variation in case outcomes and judge votes can be attributed to attractiveness, while holding other factors constant. The results show a clear, monotonic relationship: more attractive lawyers are significantly more likely to secure favorable votes and to win their appeals, with increases in attractiveness producing sizable shifts in predicted win probabilities.

The robustness checks are central to the study’s contribution. The attractiveness premium persists when substituting the machine learning measure for survey ratings, when using video-still images instead of headshots, and when focusing on advantages in attractiveness relative to one’s opposing counsel. The patterns are particularly pronounced in closer cases, consistent with the idea that judges, facing heavy dockets and constrained attention, rely on visual heuristics as secondary cues when doctrinal guidance is ambiguous. While the research does not claim that appearance dominates the law or ideology, it demonstrates that extra-legal factors can materially influence outcomes in a domain that aspires to neutrality and formality.

For legal practitioners and scholars, the study underscores that appellate advocacy is not purely about written briefs and precedents; the in-person advocate, including their appearance, plays a measurable role in how arguments are received. This has unsettling normative implications for the ideal of “blind” justice and raises practical questions about how clients and firms select oral advocates, how judges might mitigate their own biases, and how training and institutional design could reduce reliance on irrelevant cues. More broadly, the findings situate judicial decision-making within a larger behavioral framework, in which even elite courts are susceptible to the same cognitive shortcuts that affect decision-making in other high-stakes professional environments.

How the Study Advances Empirical Understanding of Legal Outcomes

The study finds that appellate outcomes exhibit structured and repeatable patterns in which extralegal cues, specifically perceived attorney attractiveness, systematically correlate with judicial votes and case outcomes across a large set of federal appeals. The analysis shows that recognizing such structure matters for understanding legal outcomes because it demonstrates how institutional decision environments with heavy caseloads and limited legal clarity can produce consistent, nonrandom effects tied to observable features of advocacy rather than to case facts alone. By combining randomized variation in advocate appearance, multiple independent measurement strategies, and case-level controls, the study reflects an empirical, evidence-driven approach to analyzing legal outcomes and decision contexts, aligning with Pre Dicta’s emphasis on rigorous case-based analysis as a necessary foundation for high-level litigation practice.

Pre/Dicta Debuts Suite of New Capabilities, Further Expanding its Predictive Insights into Judicial Decision-Making