Forecasting and demand estimation play a critical role in healthcare supply chain management as they form the foundation for effective planning and resource allocation. In healthcare, the supply chain is unique due to the high stakes involved, where the unavailability of essential medical products, drugs, or equipment can directly impact patient outcomes. Accurate forecasting enables healthcare providers to predict the future demand for medical supplies, pharmaceuticals, and other critical items, allowing them to align procurement, inventory management, and distribution processes with anticipated needs. This proactive approach helps to maintain a balance between supply and demand, which is crucial in an environment characterized by unpredictable patient inflows, varying disease patterns, seasonal illnesses, and sudden public health emergencies. One of the primary benefits of accurate forecasting in healthcare is the minimization of stock-outs. Stock-outs occur when the inventory of critical items is depleted, resulting in an inability to meet patient needs promptly. In hospitals and clinics, this can lead to delayed treatments, surgical cancellations, and compromised patient care. By analyzing historical consumption data, patient admission trends, seasonal fluctuations, and epidemiological patterns, healthcare supply chain managers can generate forecasts that predict the quantity of each item required over a specific period. This allows healthcare facilities to maintain optimal inventory levels, ensuring that essential medicines, vaccines, consumables, and medical equipment are readily available when needed. For example, during flu season, hospitals can anticipate an increased demand for antiviral medications and vaccines, reducing the likelihood of shortages that could affect patient care. Accurate demand estimation also plays a crucial role in reducing wastage, which is a significant challenge in healthcare supply chains. Many medical supplies, particularly pharmaceuticals, have limited shelf lives and strict storage requirements. Overestimating demand can lead to excess inventory that may expire before use, resulting in financial losses and environmental concerns due to the disposal of expired items. Conversely, underestimating demand can trigger emergency procurement, which is often more expensive and less efficient. By leveraging sophisticated forecasting models, healthcare organizations can align procurement decisions with actual demand patterns, minimizing both overstocking and understocking. Techniques such as time-series analysis, regression models, machine learning algorithms, and inventory optimization tools enable precise estimation of future requirements, helping to reduce waste, control costs, and improve overall supply chain efficiency. Continuity of patient care is another area where forecasting and demand estimation have a significant impact. Healthcare facilities must ensure that critical treatments are uninterrupted, especially for patients with