Abstract: Based on the basic principle of the dynamical analogue prediction, the optimal dynamic multi factor scheme is established to revise prediction errors. It is applied to predict the subtropical anticyclone in the western Pacific. The key prophase predictors for forecasting the subtropical anticyclone in summer were separated from the atmospheric circulation factors through the correlation analysis and the cross validating the anomaly correlation coefficients (ACC). Then we made the independent sample return test of 2003-2010, and the results show that the optimal dynamic multi factor schemes can help the numerical model improve the accuracy of prediction. Based on this, we extract the two typical indexes (the western ridge point and the ridge line index) for the prediction of subtropical anticyclone, which are able to represent the characteristics of the subtropical anticyclone. Then we project the two indexes on a two-dimensional plane and associate it with the statistical classification of the subtropical anticyclone. Furthermore, we get the summer precipitation distribution type of forecast years corresponding to the type of subtropical anticyclone. The result shows that the distributions of precipitation corresponding to the projection of the type of subtropical anticyclone are well consistent with the observations, indicating the rationality of this type of classification of the subtropical anticyclone and precipitation distribution. Based on this study we could further forecast the monsoon precipitation through the objective and quantitative prediction of the subtropical anticyclone and thus provide a possible scheme for improving the monsoon precipitation prediction skill.