Abstract: Grouting water plugging is one of the main means to prevent mine water disaster. Based on the grouting project of Qiuji Coal Mine in Huanghebei Coalfield, this paper scientifically analyzed the grouting effect of limestone directional drilling by XGboost, support vector machine, K-nearest neighbor and BP artificial neural network. The research shows that the model accuracy of XGboost, support vector machine and K nearest neighbor is less than 0.9, while the fitting degree of BP artificial neural network test is 0.93. The accuracy of field data test is 0.9, which proves the feasibility and accuracy of BP artificial neural network in evaluating grouting effect. Finally, an intelligent evaluation method of grouting effect based on BP artificial neural network is proposed by MATLAB, and a simple demonstration platform is made according to the model, which realizes the intelligent and rapid evaluation of grouting effect, and has a scientific guiding role for the development of mine grouting effect evaluation theory and coal safe mining.