On the basis of optimization of edge distribution function, a joint probability distribution model of extreme precipitation based on R-Vine Copula function is constructed with conditional Copula function and Vine graph structure. The model is verified and compared with the measured data of four meteorological stations in Henan Province. The risk of extreme precipitation is identified with extreme precipitation factors. The results show that this model is able to discriminate the tail characteristics among variables, with statistical characteristics, such as Kendall and Spearman correlation coefficients of the original sequences, maintained. The overall accuracy of this joint probability distribution model of extreme precipitation is better than that based on C-Vine Copula function. The probability distributions of annual precipitation and precipitation intensity, maximum 1d precipitation and maximum 5d precipitation in Henan Province are closely related. The influence of each index on the joint probability density shows spatial heterogeneity.