In this paper, we investigate the application of the Manta Ray Foraging Optimization (MRFO) metaheuristic algorithm for optimizing routing protocols within Mobile Ad Hoc Networks (MANETs). MANETs are decentralized wireless networks consisting of mobile nodes that establish temporary connections independently of any pre-existing infrastructure. Routing protocols, a critical component of MANETs, consist of rules and algorithms that manage the forwarding of data packets across the network. We propose an improved routing protocol based on MRFO, named MantaNet, to identify optimal routes for data transmission. Simulations were conducted using MATLAB software to design a dynamic network comprising nodes moving within a defined zone. The optimization problem focuses on minimizing the distance traversed by data from the sender to receiver, thereby reducing energy consumption, overload, and congestion. The MantaNet algorithm begins with a random initialization of candidate routes, which are then evaluated using a fitness function. The MRFO updating processes are applied to refine the search through multiple iterations. To assess the performance of the MantaNet approach, we conducted several simulations, varying the distance between the sender and receiver, the number of nodes, the candidate solutions, and the iterations. The results demonstrate that the proposed MantaNet algorithm consistently identifies optimal routes across various network sizes and scales. The algorithm maintains strong performance even with a small number of candidate solutions and iterations, thereby reducing computational time. Overall, the MantaNet routing method offers a promising solution for efficient data transmission in MANETs.