Abstract: The varying geological conditions of the surrounding rocks of coal mine roadways influence the wide application of full-face rock tunnel boring machines (TBMs). Therefore, accurately assessing the excavatability of rock masses in coal mines and the rock adaptability of TBMs is crucial for the efficient operation of TBMs. Based on the evaluation results of the parameters and excavatability of rock masses, this study built a classification model for rock mass excavatability using the technique for order preference by similarity to ideal solution (TOPSIS). Furthermore, combining the correlation analysis between the BQ values of different geological conditions and the utilization ratio of TBMs, this study proposed a classification model for TBM adaptability to rock layers. Moreover, this study evaluated the rock mass excavatability and the rock adaptability of TBMs based on the daily advance rate. Accordingly, it established a comprehensive classification method for surrounding rocks based on TBM performance. As indicated by the field application of this classification method based on the engineering data from the TBM excavation of a gas drainage roadway on the floor in Shoushan Mine No.1, the average monthly footage of the roadway achieved using a TBM could reach 400 m under a rock mass excavatability of Grade I and a rock adaptability of Grade 3. When the utilization ratio of TBM was less than 20%, on-site problems, such as TBM jamming and difficulties with slag discharge, were highly liable to occur. Based on the automatically collected TBM excavation data and the analysis results of surrounding rock properties, the comprehensive classification method for surrounding rocks proposed in this study can dynamically evaluate the performance of TBMs under different geological conditions of surrounding rocks, thus providing a theoretical basis for the design of the tunning control parameters of TBMs.