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This paper describes the three methodologies used by CALCE in their winning entry for the IEEE 2012 PHM Data Challenge competition. An experimental data set from seventeen ball bearings was provided by the FEMTO-ST Institute. The data set consisted of data from six bearings for algorithm training and data from eleven bearings for testing. The authors developed prognostic algorithms based on the data from the training bearings to estimate the remaining useful life of the test bearings. Three methodologies are presented in this paper. Result accuracies of the winning methodology are presented.