Abstract: The accurate construction and parameter assignment of fault zone numerical models have long been a challenge faced by coal mine geologists. The prediction of inflow from fault zones during mining activities is complicated by issues such as structural complexity and difficulty in obtaining permeability coefficients. This study focuses on the calculation of fault zone inflow under mining influence, and uses borehole survey data to construct numerical models of fault zones and study water inflow. First, a stochastic fracture generation method, in combination with the COMSOL Multiphysic finite element numerical simulation software, was used to investigate the impact of the number of fractures per unit area and unit volume on pore water pressure, seepage velocity, and permeability. The relationship between the number of fractures per unit area and unit volume and permeability in fractured rock masses was determined, and the relationship between stochastic fractures and permeability in both 2D and 3D rock masses was established. Based on borehole survey data, a functional relationship between the fractured rock mass quality index (RQD) and rock mass permeability was derived. Additionally, a 3D numerical analysis model of fault fracture zones was established based on drilling data to study the water-conducting and water inflow patterns of fault zones and goafs during coal seam mining with varying RQD values. The results indicate: The number of fractures and permeability follow an exponential function relationship. Compared to the 2D fracture model, the permeability in 3D fractured rock masses is more significantly enhanced with an increase in fracture number. A numerical analysis model incorporating fault zone structures was constructed using a method that combines linear extension of real fractures within borehole-controlled regions with RQD parameter assignment for undetected areas. This model, in conjunction with multipoint borehole analysis, enabled the establishment of an exponential function relationship between RQD and permeability, allowing for the prediction and analysis of water inflow using mining rock mass quality indicators. The findings of this study are of significant importance for water inflow prediction, prevention of sudden water inrush disasters, and safety evaluations in mines.