In the current research, a moth flame optimization algorithm (MFOA) is used to identify the best parameters of proton exchange membrane fuel cell (PEMFC). Two different PEMFCs: NedStack PS6, 6 kW, and SR-12 PEM 500W are used to demonstrate the accuracy of the MFOA. Throughout the optimization process, the seven unidentified parameters (℥1, ℥2, ℥3, ℥4, λ, ℛ, and B) of PEMFC are appointed to be decision variables. While the fitness function that needed to be minimum is represented by the root mean squared error (RMSE) between the calculated voltage of PEMFC and the experimental dataset. The attained results by MFOA are compared with the sine cosine algorithm (SCA) and particle swarm optimization (PSO). The main findings verified the supremacy of the MFOA in estimating the best parameters of the PEMFC model in comparison with PSO and SCA.