Forest Fire Prediction using machine learning and geospatial analysis. Features include data preprocessing, geospatial transformations, visualization with Kepler.gl, and evaluation of models like Logistic Regression, SVM, and Random Forest. Achieved 89% accuracy with interactive fire risk predictions.