Introduction and Study Objective According to budgetary data, the pharmaceutical inventory is a significant expense for healthcare institutions, ranking as the second-largest annual expense in their budgets. It is crucial to estimate the annual level of inventories accurately to avoid waste in resources and minimize costs. In this context, a recent study aimed to identify pharmaceutical items with high growth rates over an eight-year period and determine the percentage of wrong estimation. Study Design and Methodology The study uses a cohort retrospective study design and analyzed medical inventories data from an Enterprise Resource Planning (ERP) system. There are roughly 2077 medical items in total, some of which are unplanned requests and others have alternatives. Of these, 974 pharmaceutical products were examined in the study to generate the percentage of estimation. Result and Findings The results indicate that the departments of radiology and gastroenterology had the highest percentage of inaccurate demand estimates in their yearly inventories. Additionally, it demonstrates that the majority of the department miscalculated their yearly quantity utilized. Transferring patients to another facility is one of the many reasons why the amount of medication lent increases; in this case, KAMC is required to supply medication for the moved patient. Furthermore, inconsistent use forces KAMC to loan nearly expired medications to other healthcare organizations and re-distribute them when needed at different times. Drug items with a high percentage of borrowing are associated with poor medical services because healthcare services are interrupted and even when borrowing is done, it takes time to meet needs and affects the continuity of delivered the services. Recommendation The investigation discovered a significant difference over an eight-year period between the suggested and actual maximum levels. In order to reduce deviations in future quantities, the research team chooses to create a new amount by adding growth value to the average values of previously recorded years.