This research was designed to examine differences in the predictive power of alternative scale weighting methods in the context of job evaluation. Two different point‐factor job evaluation instruments were used to evaluate 71 managerial and service jobs in a metropolitan university, and five different weighting models were compared in terms of predictive validity and salary classification. For the job evaluation system having high multicollinearity and validity concentration, no significant differences in accuracy were found among the weighting methods. However, in the more heterogeneous system, prediction models based upon unit weights, correlational weights, and multiple regression had significantly higher predictive validity than models based upon equal raw score weights or rational weights developed by a job evaluation committee. In addition, the weighting models differed substantially in terms of the predicted policy wages and classification structure