Estimating the presence of water on the road is a crucial application when targeting safety-related issues concerning the operational life of a road stretch. Having the capability of deploying a real-time road conditions classifier may represent a powerful way to reduce the number of car accidents caused by bad weather conditions and in general may help making the drivers more aware of the surrounding environment while driving. This work describes the realization of a Machine Learning model able to estimate road conditions from on-site camera images. The project has been carried out within a collaboration between Politecnico di Torino university and Waterview srl.