Purpose of Study: This study examined the influence of two key inventory management practices Just in Time (JIT) and Vendor Managed Inventory (VMI) on the performance of supermarkets in the North Rift Region. Problem Statement: Inventory management plays a critical role in ensuring the operational efficiency and financial success of supermarkets. With growing competition and evolving consumer expectations, supermarkets in Kenya s North Ri ft Region are increasingly seeking innovative inventory management strategies to enhance performance. Methodology: A mixed methods descriptive survey design was employed, targeting 58 supermarkets in the region. The units of observation included heads of procurement, stores, IT, and finance departments, with a purposive sample of 232 respondents. Data were collected us ing structured questionnaires and analyzed using SPSS. Result: The findings revealed that both JIT and VMI practices significantly influence supermarket performance. JIT implementation led to improved operational efficiency by reducing storage costs, elim inating waste, and enhancing order fulfillment speed. VMI was found to strengthen vendor relationships, streamline inventory replenishment, and improve supply chain coordination, ultimately leading to enhanced customer satisfaction and reduced stockouts. C hallenges such as mistrust in vendor decision making and supplier delays were reported but were largely mitigated through improved data sharing and collaborative planning. The study concludes that supermarkets adopting JIT and VMI practices benefit from im proved performance in terms of operational efficiency, cost control, and customer service. Recommendation: It recommends investment in staff training, supplier collaboration, and technology adoption to support these practices. Policymakers are encouraged to develop supportive frameworks that facilitate real time data integration and transparency in supply chain operations. Further research is suggested to explore the integration of emerging technologies such as artificial intelligence (AI) in inventory opt imization.