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Gears are one of the most important parts of any mechanical transmission system, and in order to achieve reliable operation effective monitoring techniques must be employed. Predictive health monitoring (PHM) systems are currently gaining in popularity due to their effectiveness in providing robust information about the system condition and reducing maintenance costs. However, PHM systems require reliable monitoring techniques, such as vibration, acoustic emission, and oil debris analysis. These techniques have been studied in recent years to discover which can best support the operation of PHM systems in tracing the condition of the operating transmission. These studies have shown the need to apply intelligent algorithms in order to benefit from the advantage of each technique in classifying faults and predicting the onset of failure. This paper presents a new online PHM system for monitoring different gear faults using vibration analysis and autoregressive (AR) algorithms.