Wireless Sensor Networks (WSNs) have become an essential technology in many domains, from smart infrastructure development and industrial automation to environmental monitoring. However, the limited power supply of individual sensor nodes makes long-term WSN sustainability arising battle. Classifying the details of energy efficiency and maximizing energy efficiency is of utmost importance for extending the network's lifespan and guaranteeing stable operation. By combining the Low Energy Adaptive Clustering Hierarchical (LEACH) routing protocol with Proximal Simulated Annealing (PSA), this article presents PSA-LEACH, a new way to improve WSN energy efficiency. To improve energy consumption and extend network lifespan, PSA-LEACH dynamically optimizes clustering settings. In the final step, the Improved Random Forest Classifier (IRF) algorithm categorizes the energy information. The efficacy of PSA-LEACH in enhancing energy efficiency measures, including throughput, energy consumption, delay, and packet delivery ratio, is shown by experimental simulations. Environmental monitoring and smart infrastructure development are only two of the many potentials uses for the suggested method to increase the longevity and robustness of WSNs. Experimental simulations demonstrate that PSA-LEACH significantly enhances energy efficiency measures, including throughput, energy consumption, delay, and packet delivery ratio. Notably, PSA-LEACH achieves up to a 25% increase in network lifetime and a 20% improvement in throughput compared to existing energy-aware routing protocols. An exploratory study suggests that the PSA-LEACH protocol is more efficient than the existing energy-aware routing protocols regarding throughput, energy utilization, and delay and packet delivery ratio. The results underscore the exceptional performance of PSA-LEACH and its potential for significantly increasing the network lifetime of WSNs.