||The rapid development of technology in all the scientific fields has caused the convergence of them into the same science’s field. An example of this is Telematics; a synergetic combination of informatics and telecommunications. Nowadays telematics is not very common in the context of airport technologies. However, many of the paperwork, data and services are computer-based and then retransmitted to telecommunications systems. In this thesis the characteristics that surround telematics technology are studied, and the benefits of its use are analyzed through case studies. To develop models, Machine Learning and Data Science techniques have been used. These techniques allow the extraction of proper information of the data obtained by telematics. The models include different procedures, including prediction and interpretation data techniques. As a result, the application of this model could be useful in different fields or environments. In this thesis, the models are adapted to the extraction of the information about the characteristics of Telematics in Vehicles; therefore if this model is going to be used in other ambits, it should be adapted to the new context (keeping the main base). During the thesis different application uses for the model are suggested. These applications, joining data and telematics services, might provide many advantages in the ground operations management at the airport such as the fuel consumption optimization across an accurate use of the concerning features affecting the fuel waste, reducing therefore emissions and avoiding monetary penalties for the accomplishment of certain environment protocols.