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Abstract Paints and coatings undergo complex physical and chemical changes under environmental exposures, requiring accurate predictive models for reliable applications. This work presents a novel integrated approach to modeling accelerated weathering of automotive coatings by coupling concurrent physical and chemical degradation processes within a multi-scale framework that captures both macro-scale physical changes and micro-level chemical transformations. The chemical component/model simulates photodegradation reactions using chemical kinetics equations that account for photoinitiation, radical propagation, chain scission, and crosslinking, while the physical component employs Monte Carlo simulations where repeated random photon absorption events develop realistic surface erosion patterns and pit/pore formation. The integrated model demonstrates strong quantitative agreement with experimental data: depth-wise polymer concentration profiles show mean squared error less than 0.003 when validated against FTIR absorbance data, surface topography evolution including pit/pore formation and connectivity transitions is captured with fidelity, surface roughness (RMS) ranges from 0-0.85 μm consistent with literature values (0.199-0.987 μm), thickness loss progresses from initial 20 μm to complete ablation over 500 hours of accelerated weathering, and relative fracture toughness decay follows Griffith criterion with progression from 1.0 to less than 0.1 across the degradation timeline. This coupled modeling approach provides quantitative mechanistic insights into coating failure mechanisms through integrated chemical kinetics and stochastic surface evolution, enabling accurate service life prediction and serving as a computational tool for formulating more durable coatings and optimizing accelerated testing protocols.