Simplify and save: companies search for smart fleet management solutions with these two goals that enable them to manage their vehicles easily and efficiently. With this in mind, many tools have been developed, based on several indexes. Among them driving behavior is one of the most common, it is mostly used to evaluate driver safety and to minimize fleet management costs. In this thesis, a highly customizable framework has been proposed. Starting from the data provided by the devices mounted inside the vehicles (Controller Area Network), our tool can determine the driving behavior. To do this, several phases are performed whose outputs are effortlessly interpreted by a person not an expert in data analysis, as a fleet manager.