Tectonically-deformed coal (TDC) is a potential source of threats to coal-mining safety. Finding out the development and distribution of TDCs is a difficult task in coalfield seismic explorations. Based on the previous investigations, the P-to S-wave velocity ratio (α/β) is a stable parameter for the identification of TDCs and most TDCs have α/β values of less than 1.7. Here, a TDC detection method using a model-based joint inversion of the multi-component seismic data is proposed. Following the least square theories, the amplitude variation with offset gathers of the PP-and PS-waves are jointly inverted into the corresponding α/β values. The prior models generated from the P-and S-wave velocity and density logs are employed in the joint inversion to enhance the inversed models. Model test results show that the model-based inversion is of high anti-noise ability and has a good recognition ability of TDCs. The proposed method is applied to a work area of the Guqiao mine in China. The TDCs developed in coal seam 13-1 are effectively identified according to their inverted α/β values of less than 1.7. The detection result is verified by the well and tunnel excavation information.