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With increasing demands for efficiency and product quality and progressing integration of automatic control systems in high- cost mechatronic and safety-critical processes, the field of supervision (or monitoring), fault detection and fault diagnosis plays an important role. The technological development of vehicles has evolved rapidly and everything is almost controlled by electronic systems. In the field of vehicle maintenance there has been considerable work done for fault diagnosis in the last few years. With the advancement in diagnosis system it is possible to provide new kind of fault prediction services. The maintenance services take advantage of symptoms and data related to fault for diagnosis. It is important to explore possibilities beyond protective maintenance system. This master thesis studies vehicle fault prediction possibilities. We have learned about working of heavy vehicle components and their faults. In this master thesis we have investigated different techniques which can be applicable for fault prediction.