The properties of several simple forecasting decision rules which incorporate a priori knowledge are studied in this paper. Moments of these decision rule forecasts are derived, tabled, and discussed. In particular, comparisons are made with moments and mean-squared error of forecasts which incorporate no a priori information. It is found that use of prior information can lead to forecasts with mean-squared errors smaller than those associated with usual forecasting techniques provided that the prior information incorporated in the decision rule forecasts is at least reasonably accurate. Also the relative properties of alternative decision rule forecasts are assessed.