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Response Surface Methodology (RSM) when combined with the Propagation of Error (PoE) approach offers an efficient robust design able to find the best operating conditions to simultaneously maximize power density and reduce normal operation variability in a hydrogen-fed Proton Exchange Membrane Fuel Cell (PEMFC). To proceed with the statistical analysis, a central composite design with 20 experimental runs (6 central points were used to assess the experimental error) was adopted to inspect which factors have significant effects and how they interact each other. This allowed generating a polynomial function to determine the maximum power density at 1415 mW/cm 2 . Taking advantage of the desirability concept and using the PoE measure as a response, a multiple optimization under different restrictions was carried out defining a new set of operating conditions able to target the maximum possible power density at the most robust conditions (1074 mW·cm −2 at 55 °C, 50% RHC and 25 Psi). Then, actions were carried out to narrow even more the tolerance intervals towards more ambitious standards. Reducing the standard deviation from input factors through the use of adequate controlling measures led to a decrease of almost 50% in the tolerance intervals. This is an useful methodology to help the PEMFC normal operation more repeatable and predictable under its lifetime by combing both optimization and robustness goals.