Recent research in link breakage prediction-based routing protocols in Mobile Ad Hoc Networks (MANETs) focuses on proactively maintaining stable communication paths by predicting potential link failures before they occur. These studies employ techniques such as mobility pattern analysis, signal strength estimation, and machine learning-based prediction models to evaluate link stability. By estimating factors like node velocity, distance, and direction, the routing protocols can select alternative paths or trigger early route repairs, reducing packet loss and latency. Emerging approaches also integrate fuzzy logic, swarm intelligence, and deep learning to enhance prediction accuracy and adaptability in highly dynamic environments. Overall, link breakage prediction-based routing significantly improves network reliability, throughput, and energy efficiency, making it a promising direction for sustaining robust MANET operations under frequent topology changes.