The merits of double exponential smoothing are discussed relative to other types of pattern-based enrollment forecasting methods. The basic assumptions and formulas for its use are outlined. The difficulties associated with selecting an appropriate weight factor are discussed, and the potential effect on prediction results is illustrated. Two methods for objectively selecting the “best” weight factor are described and analyzed, and evidence is presented suggesting that they may be used effectively in the enrollment-forecasting process.