Uprisings are an act of resistance/rebellion. Uprisings could be the general population rising against the government (such as the protests in Zimbabwe as people protest over the poor economic conditions) or it could be people with morally questionable intentions against the general populace such as the Boko Haram in Nigeria. It is important to predict when uprisings are going to occur for the sake of peace and safety of everyone. This leads to the question of how we can possibly know before a social upheaval begins. Currently there is no official way to predict social unrest or a protest; people only know when a protest has already started. For this research, I will focus on using machine learning to study the effects of economic trends causing social uprisings. I use the trained machine learning model to predict when social upheaval’s are likely to happen. This model will be continually improved by doing exploratory data analysis to see which financial metrics are more reflective of the economy at any given time and using those metrics as input into the model. Continuously improving the accuracy of the model means we get closer to accurately predicting social unrest consequently ensuring the peace and safety of the public in the event of a protest