This study examines the statistical validation of a recently developed, fourth-generation (4G) riskāneed assessment system (Correctional Offender Management Profiling for Alternative Sanctions; COMPAS) that incorporates a range of theoretically relevant criminogenic factors and key factors emerging from meta-analytic studies of recidivism. COMPAS's automated scoring provides decision support for correctional agencies for placement decisions, offender management, and treatment planning. The article describes the basic features of COMPAS and then examines the predictive validity of the COMPAS risk scales by fitting Cox proportional hazards models to recidivism outcomes in a sample of presentence investigation and probation intake cases (N = 2,328). Results indicate that the predictive validities for the COMPAS recidivism risk model, as assessed by the area under the receiver operating characteristic curve (AUC), equal or exceed similar 4G instruments. The AUCs ranged from .66 to .80 for diverse offender subpopulations across three outcome criteria, with a majority of these exceeding .70.