Urban areas, particularly in the Krukut watershed, face a significant issue with inundation. One factor that contributes to the rise in inundation is the decrease in permeable surfaces and the corresponding increase in impermeable surfaces. Despite numerous attempts, controlling inundation in the area has not been effectively mitigated. Therefore, a predictive model is required to anticipate the occurrence of inundation in a watershed. This study aims to develop a predictive model for estimating the extent of inundation. This model aids in predicting and mitigating the rise in inundation events and runoff rates and this report presents information on the determination of the previous area in the Krukut watershed with the aim of reducing runoff. This study will employ multiple linear regression techniques to forecast the extent of inundation in the Krukut watershed. The analysis will incorporate rainfall, land use variables, and drainage system capacity as predictors. Data on inundation events from 2010 to 2020 was collected from reliable social media sources, while rainfall data from 2003 to 2018 was obtained from ST. The 2019 Citra Landsat data provides information on the land use of the UI Campus. Regression analysis was conducted using SPSS software to develop inundation area prediction models. The classical assumption test analysis confirmed that the data follows a normal distribution, allowing for the application of multiple linear regression. The analysis utilised the T test and F test to determine the impact of Building (X2) on the coverage in the Krukut watershed over a 25-year period. The results indicated a significant influence, as evidenced by the model equation Y = -0.0003 + 0.0026 X2. The test results indicate that the model application has a high level of accuracy, with a kappa coefficient value of 0.83. This suggests that the model is highly reliable and suitable for implementation in the Krukut watershed. Additionally, the model predicts that the Krukut watershed will experience flooding over an area of 17.6 hectares within a 25-year period.