Holding optimum inventory and satisfying customers demand with sufficient service level is a challenging task. To keep a good balance between inventory level and sufficient service level implementing appropriate demand forecasting model plays important role in inventory management system of spare parts. The purpose of this thesis study is to recommend a better demand forecasting approach for spare parts inventory management of MOENCO from models suggested in literatures that provides a better solution in keeping a good balance between stock holding amount and service level. Companies who implement appropriate demand forecasting model will have less tied up capital, reduce operational & overhead costs, and lower wastage of wealth due to obsolescence & scraping while satisfying customers demand with sufficient service level that helps to sustain in business with good profit. A model suggested in literatures called approximation demand forecasting model selected to simulate sample spare parts data obtained from MOENCO database. With 2 weeks aggregated demand, and 4 months lead time period optimum values of smoothing constant of demand size (Î±z), smoothing constant transaction interval (Î±i), and forecasted demand identified by simulation with Microsoft Excel, that provide the least average MAPE. Then, the stock amount and service level calculated, and compared with the existing inventory model to prove its effectiveness. It is observed that approximation model can be considered as a good managerial tool for automotive parts inventory management system of MOENCO to have optimum stock holding position with sufficient service level so that, it reduces capital tied up, enhances efficient cost management, and efficient utilization of forex with acceptable service level, and hence maximizes the profitability of the business. This thesis work can be more enhanced by testing spare parts inventory data of other similar companies using approximation method that include different demand patterns.