In one project course (CPEN 291), the primary focus was on machine learning due to the pandemic shifting the focus away from designing physical hardware. For our final group project, we implemented a web application using Python, HTML, and CSS to implement a Forest Fire Predictor in BC. The dataset we used to train our Random Forest model was taken from the BC Government. I was primarily responsible for model training and front-end development. One of the biggest issues we encountered was figuring out a way to minimize the lose and increase the accuracy in our model. We explored different solutions such as using a hybrid model and looking at similar models that were also used to predict weather patterns. In the end we were able to minimize the loss by combining both a Random Forest and Linear Regression Model.