Recent research in Reducing Routing Overhead in Mobile Ad Hoc Networks (MANETs) emphasizes minimizing excessive control message exchange and redundant route discoveries to enhance bandwidth efficiency and conserve energy. Advanced protocols such as CND-AODV and Smart-AODV integrate probabilistic forwarding, neighbor density estimation, and route suppression mechanisms to limit unnecessary flooding during route discovery. Machine learning and clustering techniques are increasingly used to predict node mobility and dynamically adjust routing decisions, thereby reducing frequent route updates. Hybrid and adaptive schemes balance proactive and reactive strategies to achieve optimal control overhead reduction while maintaining reliable data delivery. Overall, these approaches focus on intelligent route management, adaptive control message dissemination, and mobility-aware optimization, ensuring scalable and energy-efficient communication in dynamic MANET environments.