Decisions making in smart cities mobility management is based on the advice of the current state of city transit based on objective data. In this paper, the case of Figueres city is presented: we analyze data coming from a group of sensors installed in a big urban area of the city and we create predictive transit models. Thanks to this study, urban and mobility technicians will be able to know if their current actions are working properly or, on the contrary, they should do other procedures. The present paper is organized as follows: on first place, we find an introduction of Smart Mobility situation in Europe and we place Figueres in its context. To continue, the opportunity of innovation is shown by defining the problem we would like to solve based on precedents and specifying the data problem. We continue with the state of the art of technologies and software used and we describe the innovation: selection and visualization of data, analysis of a group of data delimited on specified dates which are referred only to a volume of transit of a certain group of sensors. This analysis enables the calculation of transit volume prediction. R software has been used in order to obtain results which will be discussed afterwards. Finally, conclusions are described and references which have been used are provided