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A Multiple Models Approach To Assessing Recidivism Risk: Implications for Judicial Decision Making

The Pennsylvania State University

Lynette Chow-Martin

The Pennsylvania State University

This study used a large recidivism data set to develop and validate a multiple models tool for predictingrecidivism risk. Consistent with prior research, the authors found that the multiple modelstool was more accurate than tools built using the traditional single-model approach. In addition,they demonstrated that the predicted recidivism rates produced by the multiple models toolcould be summarized in a usable format consisting of four to five statistically distinct risk classesoffering an impressive degree of base-rate dispersion. Given that public protection ranks as a primaryfocal concern of judges, the authors believe that their results justify renewed attention tothe potential uses of actuarial tools within the context of judicial decision making.

Key Words: recidivism • risk assessment • actuarial prediction • sentencing

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