Classical statistical methods and the small enrollments in graduate departments have constrained the Graduate Record Examinations (GRE) Validity Study Service to providing only validities for single predictors. Estimates of the validity of two or more predictors, used jointly, are considered too unreliable because the corresponding prediction equations often possess implausible characteristics. This study investigates two statistical methods-empirical Bayes and cluster analysis-to determine their applicability to these validity problems. Data on 6,946 students from 190 participating departments were used. It is concluded that, by using the new class of empirical Bayes methods, it is possible to obtain, at the department level, useful and reliable estimates of the joint validity of several predictors of academic performance. Further methodological refinement will allow the question of differential predictive validity to be addressed at the departmental level. The technical appendix describes the estimation problem following from the empirical Bayes model.