Urbanization presents profound challenges to coastal region infrastructure, environmental health, and ecological balance. Analyzing Land Cover (LC) changes is crucial for urban planning efforts and forecasting future growth trends. This study presents an integrated geospatial framework to analyze the spatiotemporal dynamics of urban growth in Panaji, Goa from 1992 to 2042, utilizing the Maximum Likelihood Classification (MLC) algorithm to develop LC Maps for 1992, 2003, 2013, and 2022 across four main classes—Built-Up, Vegetation, Water body, and Barelands. The Kappa values for MLC mapping showed consistently high accuracy: 0.889 (1991), 0.886 (2001), 0.890 (2011), and 0.900 (2021). During 1992–2022, Panaji experienced substantial land cover changes: built-up areas expanded from 12.97 to 46.60 km2(a 259.24% increase), vegetation decreased to 79.11 km2(a 22.7% decrease), barelands decreased to 25.38 km2(a 15.63% decrease), and water bodies decreased to 76.90 km2(a 6.89% decrease). Additionally, leveraging past LC maps from 2002 and 2012 and urban growth drivers (such as slope, elevation, and proximity), a Multi-Layer Perceptron–Markov Chain (MLP-MC) model was employed to predict future urban growth. The model incorporated drivers such as proximity to built-up areas, bare land, water bodies, vegetation, ground elevation, and slope to predict the 2022 LC map, achieving over 96.42% validation accuracy. Further, MLP-MCA projections for 2022–2042 indicate substantial growth, with built-up areas expected to extend to 72.97 km2, marking a 56.53% increase from 2022. Conversely, vegetation is forecasted to decrease by 20.71%, water bodies by 8.07%, and barelands to diminish by 12.32% during the same period. These findings underscore the critical need for computational techniques in sustainable urban planning strategies and that balance urban development with environmental conservation in coastal areas.