Abstract: In the process of epidemic transmission, individual behavior plays a key role in regulating the transmission dynamics. However, existing coupled models often struggle to adequately integrate the dynamic influence of multiple realistic factors on individual behavioral decisions, or fail to fully capture the diverse complex states during the spreading process. In order to accurately capture the interaction mechanism between individual behavior and epidemic transmission, a coupled behavioral decision-making and epidemic transmission model based on a two-layer network is proposed. Based on the SIS epidemic transmission framework, individual behavior regulates the infection rate and recovery rate of the epidemic through scaling factors. Based on the framework of game theory, the model incorporates multiple real-world factors such as social pressure, behavioral implementation cost, and disease perception, and constructs dynamic rules for individual behavioral decision-making process. A bi-directional dynamic coupling between behavior and epidemic transmission is explored, thereby enabling a more precise description of the dynamic impact of behavior on spreading. Compared to existing multi-layer network models, the proposed model significantly reduces the infection level of epidemic transmission and can depict oscillatory phenomena during the spreading process. For the established nonlinear system, the stability analysis combines Lyapunov theory with potential game methods to conduct rigorous theoretical analysis of multiple equilibria, and the correctness of the theory is verified by numerical simulation. Further, a sensitivity analysis is conducted for the important parameters in the model to offer theoretical guidance for epidemic control.