Underwater noise pollution is a significant environmental issue that can have detrimental effects on marine ecosystems. One of the main sources of underwater noise pollution is ship traffic, which has been shown to negatively impact marine animals by masking communication signals, altering their behaviors, and even causing hearing loss. In the Red Sea, ships are the main contributor to underwater noise pollution, particularly in areas with high shipping traffic. This thesis aims to understand the spatial and temporal distribution of underwater ship noise in the Red Sea using an acoustic propagation model, namely the Range-dependent Acoustic Model (RAM). RAM takes into account anthropogenic and environmental inputs including water temperature, salinity, and bathymetry to predict sound propagation in the Red Sea. By running RAM with inputs of ship traffic data, maps of underwater ship noise in the Red Sea were generated. These maps are important tools for policymakers and marine resource managers to identify areas of high noise pollution, target mitigation efforts accordingly, and guide future research on the effects of underwater noise pollution on marine life in the Red Sea.