Abstract: Grouting water plugging technology has become one of the indispensable technologies for water damage prevention to engineering treatment, and research on ultrafine materials have has also become a new direction for the development of grouting materials. In order to solve the problem of optimal selection and ratio optimization of grouting materials in mine water damage grouting treatment project, the method of single factor test combined with response surface method (RSM) was used to study the optimal ratio of superfine cement grouting materials. The slurry viscosity, bleeding rate and 7-day uniaxial compressive strength of slurry with different water-cement ratio, silica fume (SF) content and highly efficient polycarboxylate water reducer (PCS) content were analyzed through single factor test, and the optimal reference level of RSM was determined. Secondly, a quadratic polynomial prediction model with slurry viscosity, bleeding rate and 7-day uniaxial compressive strength as the response target was constructed, combination with variance, residual and response surface analyzed the influence of each response variable on the response target, and the optimal ratio of grouting materials was determined. Through comparative analyze of single factor test results, the optimal water-cement ratio, SF content and PCS content were 1∶1, 35% and 0.3%, respectively. Through RSM study, it was found that slurry viscosity, bleeding rate and 7-day uniaxial compressive strength were not only affected by a single factor, but also by multi-factor interaction. According to the established quadratic polynomial response surface regression prediction model, the optimal grouting material properties were achieved when the water-cement ratio, SF content and PCS content were 0.7∶1, 38% and 0.2%, respectively. The regression simulated prediction of slurry viscosity, bleeding rate and 7-day uniaxial compressive strength was 210.82 MPa·s, 1.0% and 12.22 MPa, respectively. The laboratory verification test results showed a high degree of consistency with the predicted model results, which further verifying the reliability of the model, and the model can be used to optimize the proportion of grouting materials.