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Chronic diseases affect millions of people worldwide, making it a significant issue for the efficient and secure management of patient data. Most traditional chronic disease management systems fail to manage data in real time and struggle with interoperability and security issues. Scientists have integrated wearable devices with sensors and AI to advance traditional approaches towards CDM. These technologies enhance the monitoring and prediction of CD but still face problems related to data security. The scenario has forced researchers to investigate blockchain technology in protecting patient data. Traditional blockchain systems face the challenge of scalability, privacy, and flexible permission control. In order to address the above issues, we propose the integration of Hyperledger Fabric into CDM systems. Hyperledger Fabric is a permissioned blockchain framework that excels in data security, scalability, and customizable access control. While this study focuses on conceptualizing a blockchain-based framework, the AI-driven components have been implemented and evaluated using real-world datasets, achieving superior results. Evaluation results demonstrate an average precision of 91.79%, sensitivity of 94.72%, accuracy of 96.00%, and F1-score of 0.92, outperforming state-of-the-art approaches. The integration of Hyperledger Fabric is suggested as a future improvement in the system to ensure tamper-proof storage and safe sharing of patient data. This addresses the critical challenges in CDM systems, thereby making this study a pioneering one that presents the transformational potential of blockchain technology with AI for chronic disease management.