This study presents an innovative approach to modeling the relationship between membrane water content and relative humidity in PEM fuel cells (PEMFCs). Water management in PEMFCs plays a decisive role in cell performance and operational lifetime; however, existing modeling approaches often fall short in terms of physical realism and agreement with experimental data. In this context, a novel hybrid mathematical model combining both asymptotic and polynomial terms to more accurately capture the saturation behavior of membrane water content has been proposed for the first time in the literature. The proposed hybrid model successfully represents both the linear and nonlinear effects of relative humidity, as well as the saturation behavior observed at high humidity levels. Furthermore, for the first time, the model parameters were determined using the Particle Swarm Optimization (PSO) algorithm. Computational results demonstrate that the proposed hybrid model outperforms the conventional model, with total error metrics of SAE 5.699 and SSE 4.501. These results indicate that the proposed model achieves high accuracy in fitting the experimental data. In addition, boxplot analyses of the parameters reveal that the optimized values are concentrated within a narrow range, indicating the robustness and stability of the model. In conclusion, this study provides a highly accurate and physically meaningful modeling tool for water management in PEMFCs, offering a reliable and practical foundation for the development of model-based control strategies and the resolution of water management challenges in fuel cell technologies.