Mobile Ad Hoc Network (MANET) is a self-organizing and flexible system. MANET systems manage sensitive data from many distinct applications in various domains. Its dynamic nature increases its vulnerability to numerous types of security threats. Many of the present approaches using indirect approaches provide false approximations of trust degrees. It is significantly required a good routing system that meets Quality of Service (QoS) standards and enhances network performance. In this paper purposed cluster-based trustworthy safe multipath routing (CTSMP-Routing) for mobile ad hoc networks (MANETs). Load balancing challenge is addressed by using a modified proportional topology optimization (MPTO) approach using geographical data related to network nodes. The Enhanced Seeker Search Optimization (ESSO) approach is used to compute trust degrees after the clustering phase considering numerous network constraints including node mobility, received signal strength, energy consumption, and cooperation rate. Assumed to be the service node, the node showing the highest degree of trust manages inter-cluster routing. We have developed a hybrid soft computing approach termed the multi-layer deep recurrent neural network (ML-DRNN) to enhance the optimal path-finding process. This method selects, among many routes between source and destination nodes, the best one quickly. The outcomes of this paper demonstrate that CTSMP-Routing provides effective protection against several attack paths within the MANET environment and displays better performance in regard to quality of service (QoS) requirements.