Several advantages to the use of factor scores as independent variables in a multiple regression equation were found. To help select the most desirable type of factor score on which to calculate a regression equation, computer-based Monte Carlo methods were used to compare the predictive accuracy upon replication of regression of five "complete" and four "incomplete" factor score estimation methods. For several levels of multiple correlation (R2=.30, .50, and .70), and for several subject-to-variable sampling ratios (3/1, 5/1, and 10/1), prediction on incomplete factor scores showed significantly better double cross-validated prediction accuracy than on complete factor scores. Moreover, the unique unit-weighted factor score was superior among the incomplete methods. (Author/CP)