This study delves into the Molluscan diversity along the Gujarat coast, India, focusing on the distribution and habitat suitability of four key species: Cerithium caeruleum, Lunella coronata, Peronia verruculata, and Trochus radiatus. Utilizing Species Distribution Models (SDMs) integrated with machine learning algorithms, we assessed the impact of environmental variables on the distribution patterns of these molluscs. Our findings reveal a nuanced understanding of habitat preferences, highlighting the critical roles of salinity, chlorophyll concentration, and water temperature. The MaxEnt model, with the highest Area Under the Curve (AUC) value of 0.63, demonstrated moderate discrimination capability, suggesting room for enhancement in capturing complex ecological interactions. The spatial distribution analysis indicated a random arrangement of species, with no significant spatial autocorrelation observed. This research underscores the significance of advanced modelling techniques in predicting Molluscan distributions, providing insights crucial for the conservation and sustainable management of marine biodiversity along the Gujarat coast.