Wireless Sensor Networks (WSNs) have emerged as a pivotal technology for various applications, ranging from environmental monitoring to smart cities. However, the constrained energy resources of sensor nodes pose a significant challenge, necessitating efficient routing protocols to prolong network lifetime. In this paper, we propose a novel multi-criteria weighted clustering protocol that improves energy efficiency in WSNs. The new protocol employs a composite weight function that incorporates multiple node and network parameters, including the residual battery level and node density. These parameters are combined for an adaptive and intelligent selection of cluster heads. By dynamically adjusting the cluster head selection process based on multiple criteria, the proposed protocol achieves a more balanced energy distribution among sensor nodes, thereby prolonging the overall network lifetime. The proposed approach is further extended to the context of Overlay Wireless Sensor Networks (OWSNs) to enhance energy optimization across both physical and virtual network layers, ensuring more efficient use of the nodes’ limited power resources. This paper focuses on the theoretical formulation and conceptual framework of the proposed protocol rather than its implementation. The work provides a rigorous analytical basis for multi-criteria weighted clustering in OWSNs, serving as a foundation for future simulation-based validation and empirical performance evaluation.