These studies have provided valuable insights into the oxidation behavior of platinum nanoparticles, but using experimental techniques the underlying mechanisms and implications for catalytic activity are often out of reach. As a result, computational studies have emerged as a valuable tool to complement experimental approaches, providing insights into the oxidation process and helping to overcome the limitations of traditional techniques. Many theoretical studies have supported the claims made by experimental investigations, elucidating the electronic and structural changes induced by oxygen adsorption on platinum catalysts. However, the computational modeling of realistic nanoparticles remains largely unexplored, with most studies focusing on idealized surfaces or perfect nanoparticles, leaving room for further computational investigation into the complexity of these systems. Here, we investigate the oxidation behavior of an experimentally reconstructed platinum nanoparticle shown in Figure which was obtained from Scanning Transmission Electron Microscopy (STEM) experimental work. These experimentally reconstructed nanoparticles have been shown to exhibit unique structural features not present in perfect nanoparticles. We use a multistep approach that combines Monte Carlo simulations with Molecular Dynamics using a fast ReaxFF 37 forcefield, to provide sufficient sampling. We then validate our results by comparing the coordination numbers and bond lengths with experimental data obtained from X-Ray Diffraction (XRD), Transmission Electron Microscopy (TEM) and Extended X-ray Absorption Fine Structure (EXAFS) measurements. We further discuss results obtained with the ReaxFF forcefield by progressively climbing the accuracy ladder, e.g. using the recent MACE-MP-0 model and linear scaling DFT calculations. Finally, we present our results which will aim to highlight multiple key aspects such as the electronic structure modifications of the nanoparticle under oxidation conditions and the difference in thermodynamic and geometric predictions between both forcefields.