 This research paper examined the use of different machine learning algorithms to identify the factors associated with road accidents in Milan, Italy. It found that age and gender were the most important factors in determining accident rates, while artificial neural networks, ANNs, were the most effective algorithm for approximating complex relationships between inputs and outputs. Generalized linear mixed effects, geolamy, and multinomial regression, MNR, were also used to build upon the results from the ANNs, providing further inciting to the underlying causes of road accidents. This article was authored by Lorenzo Musson and Muhammad Amin Elisade Maynack.