<p>Energy efficiency remains a significant challenge in Cognitive Radio Networks (CRNs) due to their resource-constrained nature and the need to maintain reliable communication. Traditional routing protocols often fail to effectively manage energy consumption, leading to faster node depletion and poor network performance. This paper introduces a novel routing approach based on an Energy Optimal Algorithm (EOA). The algorithm dynamically adjusts transmission paths based on real-time network conditions. It integrates an energy-efficient routing protocol with rate-based congestion control and clustering techniques to minimize energy consumption while ensuring reliable communication across the network. The proposed approach improves network efficiency, as demonstrated by simulations on the NS2 platform. The algorithm reduces overall energy consumption by 20%, enhances packet delivery ratios, and minimizes average end-to-end latency, all while ensuring network reliability and sustainability over long periods. This work contributes to the field of CRNs by providing an energy-efficient routing algorithm that reduces energy consumption and ensures high-quality service. The integration of rate control, clustering, and energy optimization techniques offers a comprehensive solution for maximizing energy efficiency and extending the network lifetime in CRNs.</p>