Sri Lanka’s cinnamon industry plays a vital role in the nation’s economy, but it faces significant challenges, including volatility in prices, disease management, inconsistencies in classification and misidentification of species. This research, titled Integrating Digital Technologies for Sustainable Cinnamon Farming in Sri Lanka, aims to address these issues through four key technological innovations. First, a predictive analytics system that uses machine learning algorithms and time series analysis will forecast cinnamon prices, providing farmers with real-time market insights through a mobile application and web dashboard. Second, an advanced image processing and machine learning-based system will detect and assess cinnamon leaf spot disease, Black Sooty Mold Disease, Leaf Gall Forming Louse and Leaf Gall Forming Mites Disease ensuring timely and accurate treatment recommendations to minimize crop damage. Third, an automated cinnamon-grade identification system that uses image processing and machine learning will enhance the accuracy and standardization of cinnamon grading, improving market value and quality assurance. Lastly, a species identification system will be developed to authenticate different types of cinnamon leaves using computer vision techniques, preventing fraud, and ensuring product integrity. By integrating these digital technologies, this research contributes to sustainable cinnamon cultivation, empowers farmers with data-driven decision-making tools, improves economic stability, and improves global competitiveness of Sri Lankan cinnamon products.