Forest fires are among the most destructive natural disasters, causing severe environmental damage, biodiversity loss, air pollution, and threats to human life and property. Climate change, rising global temperatures, and prolonged dry seasons have significantly increased the frequency and intensity of forest fires worldwide. Traditional forest monitoring systems rely on manual patrolling and watchtowers, which often result in delayed detection and slow emergency response. This paper presents an IoT-Based Forest Fire Early Warning System designed for real-time environmental monitoring and automatic hazard detection. The system utilizes an ESP32 microcontroller integrated with temperature, humidity, smoke (MQ2), and flame sensors to continuously monitor forest conditions. When environmental parameters exceed predefined safety thresholds, the system triggers immediate alerts through a buzzer and sends notifications via cloud integration. The system also supports GPS-based location tracking to accurately identify fire-prone areas. Experimental testing demonstrates reliable detection of abnormal temperature rise and smoke presence with quick response time. The proposed system provides a cost-effective, scalable, and efficient solution for early forest fire prevention and disaster management.