NEOM is an under-development transnational city and economic zone spread over an area of 26,500 km2 along the northern Red Sea coast of the Kingdom Saudi Arabia, bordering Jordan and Egypt. This study analyzes the meteorological parameters and air pollution dispersion over the NEOM region, based on observations and air quality dispersion modeling. The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used to simulate the fate of air pollutants. To drive HYSPLIT, high-resolution (660 m) meteorological data were generated by downscaling the National Centers for Environmental Prediction (NCEP) Global Forecasting System analysis using the Weather Research and Forecasting (WRF) model. The air pollutant emission factors (AP-42) emission inventory, from the United States Environmental Protection Agency, was used to initialize HYSPLIT. A continuous three-year dataset simulated by WRF–HYSPLIT was then analyzed to understand the spatial and temporal distributions of air pollutant concentrations in the NEOM region. Strong land and sea breezes, resulting from differential heating, dominate the diurnal dispersion and distribution of pollutants in the NEOM region. The spatial distributions of the concentrations of different pollutants, which show maximum concentrations in the spring and winter because of lower boundary layer heights. The predicted maximum concentrations of NOx (∼40 μg/m3), SO2 (∼25 μg/m3), CO (∼10 μg/m3), VOC (∼0.05 μg/m3), and PM (∼4 μg/m3) remain well within the national air quality standards recommended by the Saudi General Authority for Meteorology and Environment Protection and the Royal Commission. The estimated emissions analyzed by the model do not include background emissions (such as dust and vehicle pollution), as they are not available over this region, but only major industrial sources. Our analysis provides the information needed to understand the state of the air quality in the NEOM region, providing a fundamental contribution to the environmental impact assessment and planning in the region.