Abstract: To address the issues of large prediction errors caused by fluctuations in the particle size distribution of raw coal feed during dry separation, as well as the poor compatibility between process design and actual production, and to improve the accuracy of dry separation performance prediction, this study proposes a correction method for the particle size distribution of raw coal feed based on the Rosin-Rammler (R-R) particle size distribution curve. A correction model for the particle size distribution under varying fine coal content is established, which accomplishes key steps including curve shifting, parameter calculation, and allocation of quality indicators for each size fraction. The results show that the model can accurately reconstruct the particle size distribution characteristics of raw coal under fluctuating fine coal content, enabling dynamic correction of the particle size distribution within the range of < 6 mm fine coal content from 20%～60%. After correction, the calculated yield, ash content, moisture content, sulfur content, and calorific value for each size fraction are accurate, with the relative deviation of coal quality parameters controlled within 0.5%. This significantly reduces the separation prediction deviation caused by particle size fluctuations and effectively improves the reliability of separation performance simulation and process calculation. The proposed dynamic correction method for particle size distribution and the collaborative calculation technique for quantity and quality can provide reliable data support for predicting the separation performance of dry separators, optimizing process parameters, and coping with particle size fluctuations in actual production, thereby promoting the development of dry separation technology towards refinement and intelligence.