The water-gas shift reaction (WGSR) is an essential step in hydrocarbon reforming and hydrogen production, which requires catalysts that balance activity and stability. Bimetallic Cu–Au nanoparticles offer tunable reactivity by balancing the properties of both metals . In this work, density functional theory (DFT), kinetic Monte Carlo (KMC), and molecular dynamics (MD) simulations were combined to investigate the stability and catalytic performance of Cu, Au, CuAu (L1₀), Cu₃Au (L1₂), and CuAu₃ (L1₂) catalysts. Using DFT calculations, we optimized bulk structures and slab models to evaluate their surface energies. As expected, the Wulff construction identified the (111) as the dominant facet. Adsorption energies of key WGSR intermediates were evaluated on the (111) surface of Cu and the three alloy compositions to determine stable states and reaction energetics. Energy barriers for both the direct (redox) and associative (COOH) pathways were calculated using the machine-learning nudged elastic band (ML-NEB) method. The results indicate that increasing Au content leads to higher energy barriers. To link atomistic energetics to catalytic performance under operating conditions, a KMC model was developed using the DFT-obtained energetics. The simulations reveal that the associative pathway is the dominant reaction route and identify Cu3Au as the most active alloy composition. In parallel, MD simulations of Ar⁺ ion-beam modification were performed to assess how structural deformation affects the active-site distributions and catalytic behavior of a realistic nanoparticle. Overall, the combined multiscale approach provides an atomic-level understanding of the stability, dynamics, and activity of Cu-Au alloys in the WGS reaction, paving the way for the rational design of WGS catalysts.