Effective marine pollution management requires understanding pollutant spread. This study combines IoT sensors and Support Vector Machine (SVM) techniques for predictive analytics. IoT sensors gather real-time environmental data such as salinity, temperature, and pollutant concentration. SVM predicts pollutant paths, enabling proactive interventions to protect ecosystems. This holistic approach strengthens coastal resilience and allows stakeholders to plan pollution control and mitigation strategies.