Probability of spare components adequacy is very crucial within the method of conventional operation of companies. This paper focuses on the military’s order forecasting of standby parts which has been paid much attention in military supply line which ultimately has the impact on nationwide guard finances. Formerly used time series analysis method needs more upgrading and precision so the machine learning ensemble techniques like Bagging and Boosting are proved to be useful for enhanced accuracy and suitability. Inventory dataset related to military like the most used aircraft, period during which aircraft saw the most runs, types of weapons used, etc. can be forecasted by applying ensemble learning. The principal advantage of using Ensemble techniques is that the model’s randomness is reduced and thus perks up the precision for stipulated forecasting.