Data-driven law firm rankings to reduce information asymmetry in legal disputes

Selecting capable counsel can shape the outcome of litigation, yet evaluating law firm performance remains challenging. Widely used rankings prioritize prestige, size and revenue over empirical litigation outcomes, offering little practical guidance. Here, to address this gap, we build on the Bradley-Terry model and introduce a new ranking framework that treats each lawsuit as a competitive game between plaintiff and defendant law firms. Leveraging a newly constructed dataset of 60,540 US civil lawsuits involving 54,541 law firms, our findings show that existing reputation-based rankings correlate poorly with actual litigation success, while our outcome-based ranking substantially improves predictive accuracy. These findings establish a foundation for more transparent, data-driven assessments of legal performance.

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Publication Details

Journal
Nature Computational Science
Published
2025-10-31
DOI
https://doi.org/10.1038/s43588-025-00899-2
Citations
1
Primary Topic
Law, Economics, and Judicial Systems
Type
article
Field-Weighted Citation Impact
3.13
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article

Data-driven law firm rankings to reduce information asymmetry in legal disputes

Robert Mahari, Sandro Claudio Lera, Alexandre Mojon
1 citations
Nature Computational Science
Law, Economics, and Judicial Systems
3.13
article

Data-driven law firm rankings to reduce information asymmetry in legal disputes

Robert Mahari, Sandro Claudio Lera, Alexandre Mojon
article en
1 citations

Abstract

Selecting capable counsel can shape the outcome of litigation, yet evaluating law firm performance remains challenging. Widely used rankings prioritize prestige, size and revenue over empirical litigation outcomes, offering little practical guidance. Here, to address this gap, we build on the Bradley-Terry model and introduce a new ranking framework that treats each lawsuit as a competitive game between plaintiff and defendant law firms. Leveraging a newly constructed dataset of 60,540 US civil lawsuits involving 54,541 law firms, our findings show that existing reputation-based rankings correlate poorly with actual litigation success, while our outcome-based ranking substantially improves predictive accuracy. These findings establish a foundation for more transparent, data-driven assessments of legal performance.

Nature Computational ScienceVol. 5(11)
Codexis (United States) (US), University of St.Gallen (CH), Harvard University Press (US), Southern University of Science and Technology (CN), University of Applied Sciences St. Gallen (CH), Massachusetts Institute of Technology (US), Stanford University (US)
Openalex Percentile: Top 6%
Law, Economics, and Judicial Systems
3.13
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