The LoRa-Based Wildfire Detection System aims to create a distributed network of long-range, low-power sensor nodes capable of detecting early signs of wildfire activity, such as temperature spikes, smoke density changes, humidity drops, and other environmental shifts. Each node integrates an ESP32 microcontroller, an RFM95W LoRa transceiver, and environmental sensors such as the BME280 to collect temperature, humidity, and pressure data. The collected information is transmitted wirelessly through LoRa communication to a centralized gateway, which can then forward the data to a cloud dashboard for real-time visualization and alerts. The system is designed for deployment in remote or rugged areas where traditional communication methods, such as Wi-Fi or cellular networks, may not be reliable. One of the most notable accomplishments of this project was successfully demonstrating communication between multiple sensor nodes over a distance of at least 500 meters, showing that the system can function as a basic network of distributed wildfire monitoring nodes. One of the main challenges was maintaining reliable communication between nodes while keeping the system low-power and responsive. Future improvements include adding more sensing parameters, improving mesh reliability, integrating solar power, and reducing manufacturing cost to make the system more scalable and accessible.