Gas turbines (GTs) operating in offshore environments are highly vulnerable to performance degradation from airborne contaminants such as salt aerosols, mist, hydrocarbons, and particulate matter. This study develops and validates a computational fluid dynamics (CFD) model to optimize a multistage inlet-air filtration system for offshore GT applications, complementing prior experimental investigations. A three-dimensional CAD model of a wind tunnel housing six ASHRAE filter classes (F7, H12, E11, E10, G5, F9) was created in ANSYS Design Modeler, and simulations were performed under steady-state and transient conditions using Navier–Stokes, turbulence, and particle transport models. Contaminant mass loadings from 20–100% were evaluated at inlet velocities of 5 m/s and 10 m/s to characterize airflow distribution, static and total pressures, and filtration efficiency. Results revealed peak inlet velocities up to nine times the free-stream value, with mass flow concentration opposite the vertical inflow reaching 8.4 kg/s. Static and total pressures decreased progressively downstream, with the highest pressure drops occurring at 80% contaminant loading, indicating increased flow resistance. Transient analyses showed filtration efficiency degradation over time due to fouling. Model predictions for total pressure drop and volumetric flow rate deviated by ≤10% from experimental data, confirming robustness and accuracy. This work offers validated CFD insights into the complex aero–particle dynamics in offshore GT inlet filtration, providing a predictive framework for optimizing filter design, selection, and maintenance to enhance long-term turbine reliability and efficiency.