Many factors may inuence a vehicle speed in a road, but two of them are usually observed by many drivers: its location and the time of the day. To obtain a model that returns the average speed as a function of position and time is still a challenging task. The application of such models can be in different scenarios, such as: estimated time of arrival, shortest route paths, traffic prediction, and accident detection, just to cite a few. This study proposes a prediction model based on a spatio-temporal partition and mean/instantaneous speeds collected from historic GPS data. The main advantage of the proposed model is that it is very simple to compute. Moreover, experimental results obtained from fuel delivery trucks, along the whole year of 2013 in Brazil, indicate that most of the observations can be predicted using this model within an acceptable error tolerance.