Mobile Ad Hoc Networks (MANETs) are characterized by dynamic topology, limited battery, and intermittent connections through wireless access, significantly affecting routing performance and lifespan of the network. Traditional routing protocols are not able to adjust changes in node mobility and energy imbalance because they are based on shortest path or hop count decision mechanisms. This paper proposes an intelligent routing system using the Hunter–Prey Optimization (HPO) algorithm for optimal path selection in MANETs to address these limitations. The proposed predator-prey behavioural model generates energy-efficient, low-latency, and consistent data movement. The Hunter–Prey Optimization method defines the globally optimal routing solution with a hunter representing the globally optimal route, while the prey agents dynamically explore other candidate routes to avoid premature convergence. Using the combination of residual node energy, end to end delay, number of hops, packet delivery ratio and link stability, complete fitness function is created. The HPO routing protocol selects the most reliable route based on adapting the exploit and explore principles throughout the duration of operation in mobile environments, with repeated rounds of exploration and exploitation. This method demonstrated superior performance over traditional routing protocols and current routing protocols based on metaheuristics with regards to packet delivery ratio, average delay, energy consumption and overall network lifetime through extensive simulation testing with a range of node densities and mobility patterns.