Four methods of selecting a subset of predictors from a larger set were compared for 60 correlation matrices generated by Monte Carlo techniques. Two of the procedures were criterion-independent and two were criterion-dependent. The criterion-dependent procedures were found to be superior to the criterion-independent methods. The two criterion dependent procedures (forward and backward selection) worked about equally well except for the smallest sample size where the forward selection procedure was better.