This study presents a hydrodynamic shape optimization of the DARPA Suboff submarine hull using a discrete adjoint solver coupled with mesh morphing techniques within the computational fluid dynamics (CFD). The objective is to minimize total resistance (drag) under steady, uniform flow conditions. A baseline hull form is first analyzed using a Reynolds-Averaged Navier–Stokes (RANS) solver to establish reference resistance values. The adjoint solver is then applied to calculate sensitivity fields, identifying regions where geometric modifications yield the most significant drag reductions. Mesh morphing is employed at the mesh level to iteratively update the geometry based on these sensitivities without requiring re-meshing. The optimization process incorporates a Free Form Deformation (FFD) approach to ensure smooth and continuous shape changes. Validation against experimental data demonstrates accurate predictions of resistance for the baseline hull. Through five optimization iterations, the total drag force is reduced by 6.43%. Analysis of the optimized geometry reveals that the most effective shape modifications occur near the aft section of the hull, reducing pressure gradients and improving flow separation characteristics. The results highlight the potential of adjoint-based methods integrated with mesh morphing for fluid-exposed geometry optimization of complex underwater vehicles. This methodology provides a robust, computationally efficient framework for submarine hull optimization and can be extended to other marine vehicles and hydrodynamic objectives in future applications.