To investigate the relationship between the pore structure of coal cleats and the resistivity response, and to enhance the effectiveness and accuracy of evaluating coal cleat porosity using resistivity logging, this study analyzed the distribution characteristics of the coal cleat system based on X-CT scanning imaging technology: face cleats extend further, while butt cleats are distributed between face cleats and are approximately orthogonal to them. Digital coal rock models containing different cleat structures were generated by combining Fractal Brownian Motion(FBM) and successive Random Addition Algorithms (SRA). On this basis, the Finite Element Method(FEM) was used to simulate and study the influence of coal cleat type, dip angle, and porosity on resistivity. Finally, starting from the basic principle of the dual-laterolog iterative method, we proposed incorporating the power-law relationship between cleat porosity and the formation factor into the cleat porosity calculation process. This optimized the quantitative calculation method for evaluating coal cleat porosity using resistivity logging, forming a complete research path from microscopic structural characterization to macroscopic logging response, which breaks through the limitations of traditional methods that rely on idealized geometric models. The results show that: (1) The more developed the face cleats are, the more significantly the resistivity decreases; butt cleats also reduce coal resistivity to some extent, but their influence is less pronounced than that of face cleats. (2) When the cleat dip angle is constant, coal resistivity decreases following a power-law function as cleat porosity increases. When the cleat porosity is constant, the resistivity of coal containing low-angle cleats is significantly lower than that containing high-angle cleats. However, when the cleat porosity increases beyond a certain level, the influence of the cleat dip angle gradually weakens. (3) The cleat porosity calculated by the optimized dual-laterolog iterative method is numerically closer to the inversion results from NMR logging than the values obtained using the Aguilera cube model. Although certain deviations in the variation trend persist at different depth points, which may be attributed to factors such as localized resistivity anomalies caused by coal seam heterogeneity, the influence of fracture connectivity differences on conductive pathways, and limitations in X-CT scanning resolution, the overall evaluation effectiveness of coal cleat porosity based on conventional resistivity logging is improved. The calculation accuracy meets the requirements for coal seam log interpretation and can provide an important reference for coal reservoir resource assessment.