Sultan Hasanuddin International Airport is an airport with a unique topography, making the process of rainfall formation at this airport very dynamic. To ensure safe flight operations at Sultan Hasanuddin International Airport, rainfall forecasting is needed using fuzzy logic methods, with input data influencing rainfall formation, such as precipitable water, relative vorticity, and divergence. In this study, the data used for applying fuzzy logic can be divided into three types: training data (for developing the fuzzy logic method), validation data (for validating the fuzzy logic method), and testing data (for testing the fuzzy logic method). Therefore, validating the fuzzy logic method to obtain results and accuracy of rainfall events, as well as testing the fuzzy logic method for rainfall event forecasting, are the goals of this research. The precipitable water, relative vorticity, divergence, and rainfall data in this study are divided into three types: training data (2010 – 2021), validation data (2022 – 2024), and testing data (2025 – 2030). The validation results for 2022 – 2024 were dominated by non – rain events, with 7.051 occurrences, while there were 948 occurrences of rain events. The accuracy of the fuzzy logic validation method was found to be 78.58% during 2022 – 2024, allowing the fuzzy logic method to be applied for forecasting rainfall events in 2025 – 2030, beginning with the creation of input data using the moving linear regression algorithm. The forecasting results for 2025 – 2030 using the fuzzy logic method were dominated by non – rain events, with 15.232 occurrences, while there were 2.296 occurrences of rain events.