Maintaining air quality in operating rooms is critical for infection control and patient safety. Particulate matter, originating from surgical instruments, personnel, and external sources, is influenced by airflow patterns and ventilation efficiency. This study employs Computational Fluid Dynamics (CFD) simulations using Simcenter STAR-CCM+ 2410 to analyze airflow and particulate behavior in a surgical-grade operating room. A steady-state solver with the k-ε turbulence model was used to replicate airflow, while the Lagrangian multiphase method simulated particle trajectories (0.5 µm, 1 µm, and 5 µm). Simulation results closely aligned with experimental data, validating the model's accura-cy in predicting particulate transport and deposition. Findings confirm that optimizing airflow can achieve ISO Class 7 cleanroom standards and highlight the potential for fu-ture studies incorporating dynamic elements, such as personnel movement and equip-ment placement, to further improve contamination control in critical environments.