Abstract: Owing to the accuracy of traditional Fuzzy Neural Network（FNN） forecasting model is limited by the existence of multicollinearity among matrix samples,a novel FNN model is proposed where the conditional number algorithm is used,and the training samples are chosen by means of similar coefficient computation. The case computational results of regional mean rainfall show that the mean absolute error of independent samples of 49 days for the novel FNN prediction model is 7.33 mm,and under the condition of same predictors and prediction samples its prediction error is 5.9%,14.9% and 13.4% lower than those for FNN forecast model,stepwise regression forecast model,and T213 numerical weather forecast products from China Meteorological Administration,respectively,thus showing a good prospect of operational application.