Abstract: In terms of the dataset of the second generation climate prediction model of Beijing Climate Center, BCC_CSM1.1(m) hindcasts in February from 1991 to 2010, the model is assessed on its performances in predicting five monsoon indices including the East Asian summer monsoon index (EASMI), the western North Pacific summer monsoon index (WNPSMI), the East Asian monsoon index (EAMI), the Indian summer monsoon index (ISMI) and the East Asian summer monsoon intensity index (EASMII). A correction method based on the empirical orthogonal function (EOF) analysis and the analogue analysis, called the empirical orthogonal function-analogue correction of errors (EOF-ACE) is used to correct the modes which are poorly predicted by the model.Through EOF analysis, the coordinated variation of the five monsoon indices can be reflect by the obtained modes. In addition, according to the principle of ensemble forecast, three similarity indices are used to select the similarity years. The correction process is divided into two parts, which are linear component correction and non-linear component correction.Assessments indicate that the EASMI and the WNPSMI are predicted well by BCC_CSM1.1(m). However, the prediction result of EAMI, ISMI and EASMII is poor. Through EOF-ACE correction, the model prediction skill of the monsoon indices originally unreasonable are improved, but it's unsatisfactory for the rest indices. The linear component correction mostly shows higher skill than non-linear component correction in cross-validation. However, for independent validation, the effect of non-linear component correction is mostly better than linear component correction, which displays application prospects.However, the EOF-ACE has barely effects on indices whose deviations are originally small, and correlation coefficients of some summer monsoon indices between observations and predictions are still not significant through correction. It is necessary to make further analysis on the inter-annual variation of those indices, and look for the relevant external force factors.