Since the prediction model is influenced by the multicolinearity of the selected factors and the unstability of the correlated coefficient, principal component analysis is used in this paper. Along with the compound factors of pricipal components of primary selected factors and the periodic components of prediction factors as well as the principal components itself, a stepwite regression model for predicting winter wheat yield in the major winter wheat areas of North Chian is established. Both its fitness and feasibility are better than those of the ordinary stepvvise regression models.