Recently, predictive neural network models (PNNM) have proven successful in various speech recognition tasks. But, they suffer from poor discrimination for acoustically similar speech signals. In this paper, a new discriminative training algorithm based on the minimum-error-rate decision rule is proposed. Experiments on the Korean digits recognition have shown 37.5 % reduction of the number of recognition errors.