This project aims to develop a software application that predicts high-risk crime locations and times using historical data, intending to improve urban design and safety using computer vision. Motivated by the human desire to forecast the future and advancements in machine learning, various data mining and sanitisation methods are employed to process the data and create less biased models. However, implementation challenges reduced the project scope, focusing on approximating crime locations and times. Inspired by previous crime-related forecasting initiatives, such as the Chicago Crime Prediction project, the chosen dataset comprises stop-and-search data from the UK police department's official website. The data includes information on stop-and-search incidents in the City of London between December 2019 and November 2022, providing insights into trends and patterns to predict future crime occurrences.