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With recent advances in device fabrication technology, economical deployment of large scale sensor networks, capable of pervasive monitoring and control of physical systems have become possible. Scalability, low overhead anti distributed functionality are some of the key requirements for any protocol designed for such large scale sensor networks. In this paper, we present a protocol, Distributed Predictive Tracking, for one of the most likely applications for sensor networks: tracking moving targets. The protocol uses a clustering based approach for scalability and a prediction based tracking mechanism to provide a distributed and energy efficient solution. The protocol is robust against node or prediction failures which may result in temporary loss of the target and recovers from such scenarios quickly and with very little additional energy use. Using simulations we show that the proposed architecture is able to accurately track targets with random movement patterns with accuracy over a wide range of target speeds.