The rapid advancement of 5G technology and big data analytics has revolutionized healthcare, enabling real-time monitoring, predictive diagnostics, and personalized treatment plans. Diabetes, a chronic and prevalent metabolic disorder, requires continuous monitoring to prevent complications. Traditional methods of diabetes management are often inefficient, requiring frequent clinical visits and manual data logging. This paper proposes a 5G-enabled smart diabetes management system that leverages healthcare big data clouds for real-time, personalized diagnosis. The proposed system integrates wearable biosensors, cloud-based data storage, AI-driven analytics, and 5G ultra-low latency connectivity to provide seamless patient monitoring. The system enables remote monitoring of blood glucose levels, automated alerts for abnormal fluctuations, and AI-driven treatment recommendations. By utilizing machine learning models, the system predicts potential diabetes-related complications and provides preventive measures. The research highlights the advantages of integrating 5G networks with big data clouds for a smarter, patient-centric approach to diabetes care. The experimental results demonstrate the efficiency of the system in improving patient outcomes through real-time monitoring and personalized intervention.