Abstract: Various embodiments analyze the application of satellite imaging and deep learning in predicting ignition and spread of major wildfires. The training data comes from NASA satellite products and historical records of wildfires in the United States. A state-of-the-art technique in neural network image classification may be utilized and yield impressive results for wildfire ignition prediction. In one embodiment, the model may achieve an accuracy rate of 93.5%, a precision rate of 93.2%, a recall rate of 88.9%, and an F-1 score of 90.8%. Direct applications of the model may include wildfire monitoring and wildfire prevention.