The study titled “Smart Supply Chains and Logistics Optimization through Business Analytics” explores the role of business analytics in improving logistics efficiency, operational performance, and decision-making within modern port and supply chain ecosystems. The study addresses growing challenges in logistics management such as uneven cargo distribution, fluctuating demand patterns, forecasting uncertainty, and inefficient resource utilization in Indian port operations. The primary objective of the research was to analyze cargo throughput trends, regional logistics performance, customer cargo behavior, and revenue relationships using analytical and predictive techniques. The study adopted an analytical and descriptive research design based entirely on secondary quantitative data collected from government reports, port authority publications, annual reports, and logistics databases related to selected Indian ports. Business analytics tools including Microsoft Excel, Power BI, and statistical techniques such as descriptive statistics, Chi-square test, Z-test, regression analysis, and time series forecasting were used to evaluate operational trends and logistics performance. The findings revealed stable monthly cargo throughput with consistent operational performance and a strong upward growth trend in annual cargo movement. The study also identified a significant relationship between customer type and cargo type, while regression analysis confirmed that cargo throughput has a strong positive impact on revenue generation. Forecasting results further indicated increasing future cargo demand, highlighting the need for infrastructure expansion, operational optimization, and analytics-driven planning. The study emphasizes that integrating business analytics, forecasting systems, and predictive modeling can significantly support smart logistics management, sustainable supply chain growth, and strategic decision-making in modern port ecosystems.