This study presents the development of an Internet of Things (IoT)-enabled smart energy monitoring system integrated with machine learning techniques to provide real-time energy consumption tracking and predictive analytics. The system collects electrical usage data through IoT-based energy meters and transmits the information to a processing unit for analysis. Machine learning algorithms are applied to identify consumption patterns and forecast future energy usage. The proposed system aims to enhance energy efficiency, reduce unnecessary consumption, and support data-driven decision-making. Results indicate that the system can effectively monitor real-time energy usage and provide reliable predictions, demonstrating its potential for smart energy management applications.