Abstract: To enhance the accuracy and efficiency of predicting sonar detection distance in high-complex marine environments, an improved Transformer-based modeling method for transmission loss and sonar detection distance is proposed in this paper. This method can accommodate the differences in transmission losses across various positions and directions in complex marine environments, and can precisely and rapidly predict multi-point and multi-directional sonar detection distances based on sonar equations and active/passive operating modes. Taking the transmission loss data calculated in the real large regional marine environment as input, by incorporating bidirectional long short-term memory (Bi-LSTM) network with the self-attention mechanism of the Transformer architecture, the proposed model is able to accurately capture both local details and global features in response to environmental variations. Experimental results show that the outcomes predicted from this model exhibit good consistency with the detection radii derived from the sonar equation coupling integration method. Additionally, the computational efficiency is improved by approximately 1000-fold, significantly improving the efficiency of predicting sonar performance.