Based on the rain gauge of summer daily precipitation over HuangHuai Region from 1961 to 2010, the REOF method and ttest are employed to divide the HuangHuai Region into five areas. The ttest of the five areas shows that the five areas have the significant differences, which illustrates the correctness of the division. Based on this, the summer probability regression prediction equations of the five representative sites in the five areas are established using the daily rain gauge data and the daily precipitation reforecast products of CFSv2 numerical model from June to August during 1999-2007, and related verification was carried out by the deterministic and probabilistic way. The deterministic verification of precipitation probability forecast equations established by five representative stations shows that the Threat Score of logistic regression precipitation probability equations is higher than that of the CFSv2 model and the ensemble average of T213 ensemble prediction, the false alarms rate is lower than that of the CFSv2 model and the average of T213 ensemble forecast, but the missing rate of logistic regression is slightly higher. In this paper, the probabilistic forecast verification of precipitation probability forecast equations shows that the Brier Score of logistic regression is lower than 0.2, which is much lower than that of the probability of forecast of T213 ensemble forecast. This implies that the logistic regression has higher reliability. The Brier Score Skills of the logistic regression precipitation probability forecast equations for five stations are bigger than 0.0, which means the prediction skills of precipitation probability forecast for the five representative stations are higher than those of climatical probability, higher than those of the T213 ensemble forecast. Therefore, logistic regression precipitation probability equation based on the partition is an effective and feasible method.