Comprehending wave dynamics is essential for coastal management, maritime navigation, and catastrophe planning. Four widely used wave prediction models the Shore Protection Manual (SPM), Coastal Engineering Manual (CEM), Sverdrup-Munk-Bretschneider (SMB), and Pierson-Moskowitz (PM), have their accuracy evaluated in forecasting wave height and duration at Galesong Beach, South Sulawesi. The findings demonstrate significant seasonal dependencies, with DJF displaying the greatest wave energy due to monsoonal winds. Statistical validation using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), bias, and R² indicates that the SPM and CEM models provide the most precise wave height forecasts, with RMSE values of 1.44 m and 1.61 m, respectively. The SMB and PM models exhibited greater error margins, especially in wave period estimates, rendering them less appropriate for accurate forecasting in this area. A regression study further substantiates that whereas SPM and CEM proficiently encapsulate seasonal patterns, enhancements are requisite to augment the precision of severe wave occurrences. The findings underscore the necessity of selecting suitable wave prediction models in accordance with regional meteorological conditions. This research highlights the necessity for calibrating models according to specific seasons and utilizing high-resolution datasets to improve forecasting accuracy. Future research should employ advanced statistical corrections and machine-learning techniques to enhance wave predictions and facilitate the design of sustainable coastal resilience.