Abstract: Research on coal flow characteristics based on sensors is limited by the restricted monitoring range of sensors, making it impossible to study the coal flow characteristics of the entire scraper conveyor. Additionally, research on coal flow characteristics based on model simulations often lacks consideration of mining processes, preventing the prediction of the spatiotemporal distribution of coal flow across the entire scraper conveyor. To address the issue of difficulty in monitoring the coal flow characteristics of the entire scraper conveyor in a fully mechanized mining face, this study integrated the mining process of the fully mechanized face. By analyzing the processes of coal cutting and loading by the shearer and the coal transportation by the scraper conveyor, a mathematical model for the instantaneous loading volume and cross-sectional area of the scraper conveyor under different loading methods in various process segments was established. The coal flow transportation process of the scraper conveyor was divided into coal flow translation and loaded coal flow superposition, and a spatiotemporal distribution prediction model for coal flow on the fully mechanized face scraper conveyor was developed based on the finite element method. Using this model, the spatiotemporal distribution characteristics of coal flow on the scraper conveyor during the mining process cycle were analyzed through simulation. Compared to the normal cutting stage in the middle, the spatiotemporal distribution of coal flow was more complex during the cutting stage at the ends. The maximum cross-sectional area of the loaded coal flow in the middle trough occurred during the stage of drum swapping. The volume of coal flow transported by the scraper conveyor changed in opposite trends during the upward and downward movements of the shearer, with the trend determined by the shearer's traction direction. Actual operating data from a shearer and scraper conveyor in a mine were used as input parameters for the model, and the coal volume was calculated based on the predicted spatiotemporal distribution. The results showed that the predicted trend of coal volume was consistent with on-site measurements, with a cumulative coal volume prediction error of 9.24%. The coal volume prediction errors during the fixed time periods of the shearer's cutting process and upward movement stage were 13.19% and 13.78%, respectively, demonstrating the accuracy of the spatiotemporal distribution prediction model for coal flow.