Abstract: In this paper,a stepwise multiple regression procedure is used to screen from a large number of predictors that are most significantly related to a particular pcedictand.If or more predictors are not statistically significant,they may be eliminated from equation.The stepwise technique is here used to solve the problem of monthly and seasonal forecasting of precipitation over China.As an example,from the mid-summer data of 31 years (1932-1962),the summary of the calculation procedure of monthly ptecipitation over North China is illustrated.The analyses indicates that the monthly precipitation in each tract is related to different predictors,such as solar radiation indices,parameters of general circulation,and other factors for the periods prior to rainfall.The linear regression equations (for predicting the monthly precipitation over several regions of China) based on these correlations are tested on an independent sample including 42 cases.The results are compared with those generated by chance.It is found that the prediction scores are higher than above verification standard.Finally,a brief discussion is given concerning the improvement of regression analysis and suggestions are made for further statistical work on that problem.