Equipment costs constitute the greatest majority of overall costs for semiconductor manufacturing. Therefore, maintaining high equipment availability has been regarded as one of the major goals in the industry. The ability to forecast correctly equipment preventive maintenance (PM) timing requirements not only can help optimizing equipment uptime but also minimizing negative impacts on manufacturing production efficiency. This research used grey theory and evaluation diagnosis to construct a PM forecasting model for prediction of PM timing of various machines. The results showed significant improvements of PM timing predictions compared to the existing method based on experience and an alternative method proposed by Li and Chang (Semiconductor Manufacturing Technology Workshop 2002: 10–11, pp. 275–277) for the same fab cases.