In the field of computational electrochemistry, methodologies are still maturing, and predicting electrochemical properties is difficult. This is the consequence of both cost and numerical complexity linked to the modelling of reactions in an electrochemical setup where the potential is a crucial variable. Therefore, computationally elucidating the complex interplay between the various factors governing the ORR is most challenging. In this work, we start by generating oxidized configurations of an experimentally reconstructed Pt 353 nanoparticle by performing Grand-Canonical minimization Monte Carlo simulations using the recent MACE-MP-0 foundation model. Building upon these results, we use simple arguments to compute thermodynamic and structural properties versus potential. Our model correctly predicts the formation of a stable oxide-like phase at high potentials with the presence of a place-exchange mechanism occurring at 1.06 V vs. SHE close to the onset potential of the ORR, in good agreement with experimental estimates. Additionally, using previously established scaling relations we find the Rate Determining Step (RDS) on the oxidized catalyst to be the initial reduction of O 2 to OOH * . Finally, we discuss contrasting views, with the reported possibility of non-oxide oxygenated species on specific catalysts, leading to increased activity.