Communication is an integral part of society and mobile communication has become the focus point for information exchange. The term ‘Mobile’ is backbone of wireless communication and ‘Mobility’ has revolutionized the communication itself. The user location is difficult to pinpoint because of its inherent dynamic nature. But, the GPS technology integrated into mobile devices makes it an exact science. The mobile clients’ mobility can be predicted through the usage of historical trajectories. The knowledge of the mobile client’s location to service provider has become an asset to deliver context relevant timely information. The Markov Model (MM) and Hidden Markov Model (HMM) are time tested prediction techniques used in many fields. In this paper we present mobility prediction with HMMs. The HMM is trained using real-world historical trajectories of GeoLife project by Microsoft.