This study presents the development of a strategic framework aimed at optimizing the Philippine Army Warehousing and Inventory System (PAWIS) through the integration of cloud and edge computing technologies. Recognizing the critical need for efficient inventory management in military logistics, the framework leverages the collaborative advantages of cloud-edge computing to enhance real-time data processing, reduce latency, and improve decision-making accuracy across all units. By employing advanced predictive analytics tailored to diverse demand patterns, the system addresses challenges such as inventory accuracy, resource utilization, and operational responsiveness. The proposed approach improves processing time, stability, and overall efficiency compared to traditional inventory methods, enabling timely and precise inventory monitoring and replenishment. This framework also supports decentralized data handling at the edge, ensuring faster response to dynamic warehousing conditions and minimizing data transmission overhead. The findings demonstrate that adopting cloud-edge collaborative computing can significantly optimize inventory management performance, reduce operational costs, and enhance service levels within the Philippine Army’s logistics network. This research provides a scalable and adaptable model for modernizing military warehousing systems, contributing to sustained operational readiness and strategic resource management.