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Observation of maintenance programs in healthcare facilities is an essential requirement for almost all equipment in order to guarantee its performance, prevent sudden failures and to extend the equipment's life expectancy. In this work availability, reliability and performance efficiency were used for equipment performance judgment, in order to support the clinical engineer's decision making process. Time series models were the suggested technical tools used for prediction. Two models were used in this study. Raw data were processed in an excel sheet and used as input data to Autoregressive Moving Average (ARMA) and Linear Predictive Coefficient (LPC) filters. The two models produced good prediction results compared to real data. The ARMA model resulted in the minimum mean square error compared to the other model.