Proton exchange membrane fuel cell (PEMFC) designs include multiple variable quantities with various nonlinear factors, which must be determined precisely to guarantee reliable modeling. The characteristic model of fuel cells (FCs) has an essential role in examining these cells' effective investigation. The FC design substantially influences simulation investigations of such methods, which has emerged in various applications. In this paper, a new identification method for the parameters' of the PEMFC is proposed based on using Gorilla Troops Optimizer (GTO). The optimized fitness function in the proposed method is used by the minimum value of the sum of squared errors (SSEs) of the current and estimated voltage cases. Various test cases are utilized to validate the effectiveness of the proposed method. After carrying many independent runs, the comparative algorithms are analyzed using SSEs, and the standard deviation measures. The high ability of the proposed method is investigated using steady-state and dynamic situations. The results showed that the proposed method got promising results and achieved better performance than other well-known comparative methods.