Abstract: Predicting and preventing abnormal mining pressure manifestations that affect the normal progress of fully mechanized mining face is an effective measure to reduce the hidden dangers of roof accidents in working face. A reasonable and effective method for analyzing measured mining pressure data is one of the key technologies. Based on the 3-Dimensional Surface Integral theory, a mining pressure data analysis model is proposed by introducing the Kriging Interpolation Algorithm to “search for large manifestations and focus on abnormal points”. A 3-dimensional curved top column is formed by comparing the pressure of the top plate and the pressure of the bottom plate, and a 2-dimensional coordinate surface is formed by the number of the support and the footage. Based on the 3-Dimensional Surface Integral, a mining pressure measurement data analysis model is established, and the pressure curve projection algorithm is used to analyze and predict the mining pressure measurement data. The analysis of mining pressure monitoring data for the 12514 working face of Bulianta Coal Mine in Shendong Mining Area is carried out, and obvious mining pressure areas, 3-dimensional surface projection models of mining pressure, and real-time mining pressure cloud maps are obtained. Significant pressure areas are extracted 8 times, pointing to the No.62 to No.98 support areas 6 times. The average continuous distance of the significant pressure areas is 11.9 meters, indicating that the 3-Dimensional Surface Integral Analysis Model can select areas with more intense roof movement, which has stronger pertinence compared to traditional statistical analysis methods. This validates the reasonable reliability of the proposed analysis model.