Clustering strategies show significant promise in reducing energy consumption within Wireless Sensor Networks (WSNs), ranking among the most effective techniques. However, many energy-efficient innovations are considered economically nonviable despite offering improved performance. Among existing methods, the fuzzy logic-based clustering algorithm stands out by simulating human decision-making and converting multiple input parameters into a single output. This research presents a Fuzzy Logic-Based Energy-Efficient Clustering algorithm. The proposed system evaluates the likelihood of a node becoming a cluster head by analyzing its residual energy and cumulative distance metrics. Several preliminary tests were conducted before a detailed experimental evaluation to validate the fuzzy logic-based approach. The results indicate that the system achieves higher energy utilization efficiency. Furthermore, this algorithm outperforms other clustering techniques such as LEACH and PEGASIS based on comparative results. Overall, the proposed method demonstrates improved performance and energy savings, making it a strong candidate for practical and scalable WSN implementations. © 2025 Elsevier B.V., All rights reserved.