A forecasting model for logistics demand was presented to overcome the limitations of single goal forecasts of logistics demand and forecast data complexity. Based on the forecasting evaluation index and pretreatment of rough set theory, a multiinput and multioutput wavelet network (MMWNN) model for forecasting multielement regional logistics demand was studied. The network configuration was confirmed using the stepwise checkout and iterative gradient descent methods. After rough set reduction, the evaluation index was used to forecast the multielement regional logistics demand. The results of the numerical example indicate the feasibility and effectiveness of the model.