A NTUA Diploma Thesis titled “Predicting driver behaviour in a cross-country naturalistic driving study using machine learning techniques” was recently presented by Giannis Roukos. For this reason, valuable data on driver behavior were collected through a driving experiment conducted under real-world conditions in Belgium and the United Kingdom. In the initial analysis, the importance of the variables was calculated using the “Random Forest” algorithm, based on which nine input variables were selected for further analysis. Findings suggest that the average speed of the vehicle was identified was the most significant variable, while sudden driving events, including both harsh acceleration and harsh braking, were found to significantly influence the classification of driving behavior as dangerous.