To address the scarcity of point cloud datasets in foggy weather, an optical model-based foggy weather point cloud rendering method is proposed. First, a mathematical relationship is established between the LiDAR impulse responses during good weather and foggy weather in the same scene. Second, an algorithm is designed using laser attenuation in a foggy weather, and the visibility of the rendered point cloud is set by modifying the attenuation coefficient, backscattering coefficient, and differential reflectance of the target in the algorithm to obtain the rendered point cloud of the foggy weather under the set visibility. Experiments reveal that the proposed method effectively renders foggy weather point cloud with a visibility within 50?100 m, and that the method shows stable results. Compared with the real foggy weather point clouds, the average values of KL (Kullback-Leibler) dispersion of the rendered point clouds are less than 6, the average values of the percentage of Hausdorff distance less than 0.5 m are not less than 85%, and the average values of the mean square error distance are less than 8, proving the feasibility of proposed method. Therefore, the proposed method can render foggy weather point cloud under good weather and overcomes the lack of foggy weather point cloud datasets and visibility data.