The identification of fine design trends in ship design is associated with the accuracy of computational methods, therefore, optimization schemes based on viscous flow solvers have steadily increased their share in modern hydrodynamics research and vessel design [1]. Nevertheless, hull-form evaluation under the potential-flow assumption continues to offer advantages in terms of computational efficiency and numerical accuracy when compared with (U)RANS methods, and therefore retains an important role within simulation-based design optimization (SBDO) framework. Most inviscid methods produce acceptable results for the major part of the boundary layer along the hull, while all have trouble modelling the flow near the stern where the viscosity effects are pronounced due to rapid geometrical hull changes. Meshing constitutes a key aspect at hydrodynamic numerical simulations and it is hard to determine beforehand mesh fineness suitable to resolve, physically and numerically, the main flow features at different speeds. The potential flow codes employed within this paper discretize the vessel hull, its wake and the free surface using quadrilateral panels at varying densities and utilize Rankine sources for the evaluation of vessel resistance and free surface elevation. As the number of panels increases, the grid refinement is improved, leading to more reliable results. A set of potential flow grids within a wide range of densities processed by three different codes, SWAN-2 [2] , WARP [3] [4] and SHIPFLOW [5] will be assessed and evaluated for their fidelity and accuracy by the viscous RANS solver MaPFlow [6] implemented on a suitable grid size and density. The hull form of the Kriso Container Ship KCS will be used in this investigation. The results will include comparisons of the wave-pressure, wavecuts, wave pattern, potential streamlines, and pressure and velocity contours in critical regions of the bare ship hull under investigation. The systematic grid-refinement studies are conducted to assess numerical convergence and the sensitivity of the predicted flow features to discretization effects. The numerical results will be compared against published towing-tank model experiments.