In the battery field, our research group in Amiens pioneered multiobjective optimization of battery electrodes. For instance, two papers from our group , used ML-assisted optimization of battery manufacturing by physics-based simulations and optimization of carbon felt electrodes microstructure by applying lattice Boltzmann method and Bayesian optimizer, respectively. In this paper, we take inspiration from these previous battery works, to address the complexities inherent to the GDL microstructure, such as the electrical and thermal conductivities and diffusivity, by extending further the approach to account for numerous input parameters. The novelty of our work herein lies in its proposal of a multi-objective optimization of manufacturing parameters for improving the properties of the GDL microstructure (Figure ). The optimization process seeks to strike a balance between minimizing contact resistance between GDL and MPL and maximizing electrical conductivity, thermal conductivity and diffusivity. Through these optimizations, we aim to achieve enhanced gas transport, water management, efficient current collection, and thermal regulation. This will facilitate the optimal distribution of reactant gases to the catalyst layer, ultimately promoting the overall efficiency and durability of the GDL and consequently, the performance and longevity of the PEMFC.