Based on numerical values with respect to factors influencing shares of existing products and a new product evaluated by more than one people, a structured neural network calculates predictive shares of the new product predicted by the respective persons. Comprehensive evaluations on the respective products and the new product are calculated for each person, based on the numerical values with respect to the respective factors. Correlation coefficients between the comprehensive evaluations on the respective products by the respective persons and the actual shares are calculated. The predictive shares calculated by the structural neural network are layered out in accordance with the correlation coefficients for the respective person. Average values of the predictive shares and confidence intervals are calculated for the respective layers, and based on them and the calculation result obtained by the structured neural network, a share of the new product is predicted.