Vendor Managed Inventory (VMI) system is a method in which the purchase orders are made by the supplier according to the demand data shared between the retailer/ customer. This paper provides an improved mathematical model for a two-echelon vendor-managed inventory (VMI) system with one supplier and multiple buyers. With existing VMI models based mainly on single-supplier and single-buyer systems, the new model gives an optimal realistic and scalable extension by considering various downstream buyers with different demand rates, cost functions, and lead times. Two alternative inventory control methods are considered: the traditional (decentralize) model with buyers maintaining their inventories independently and the VMI system where the supplier handles the replenishment of inventory for all buyers. The goal is to minimize system-wide total inventory cost, including setup, holding, transportation, and backorder costs under continuous review (𝑄, 𝑟) policies. Here, I have explored a problem in real-life context with sensitivity analysis to cross-verify the model and determine extent points—parameter conditions where both the systems have cost parity. Findings indicate that cost parity could be present under certain setups, yet the VMI model presents better strategic advantages in terms of coordination, visibility, and responsiveness. This research adds a real-world decision-support instrument for supply chain managers to consider when deciding whether to switch from classical stock systems to centralized VMI strategies within multi-buyer settings.