Ship hydrodynamic performance prediction in waves is a common practice in the early stages of the ship design process as the interaction between the ship and waves may adversely affect the hydrodynamic responses of the ship in comparison to calm water. Various well­established numerical and experimental methods are often utilized for prediction of ship performance in waves. Although the model tests are expensive and time­consuming, a high level of accuracy is often achieved in such experiments. On the other hand, with respect to the increased computational power, prediction of ship performance in waves by the numerical methods based on Computational Fluid Dynamics (CFD) techniques are gradually acquiring more popularity. However, the validity of the incorporated discretization schemes and modelling assumptions in these state­of­the­art CFD methods are often overlooked and the method accuracy is mainly assessed through the validation of the results based on the respective model test data. Validation as an engineering exercise aims to show that the right equations are solved, while verification (mathematical exercise) is required to demonstrate that equations are solved right [1]. The eventual objective of this research is to perform verification and validation exercises of a ship performance prediction in regular head waves using CFD, whereas in this paper, the working progress is presented which may be subjected to significant revisions. To this end, extensive attempts have been made to investigate numerical wave propagation without the presence of the hull. Ship responses in waves are significantly influenced by the wave excitation forces. Therefore, not only high level of accuracy is required for the simulation of the numerical waves, but also quantification of the numerical uncertainties are of a great importance. This becomes even more challenging when the ship hydrodynamic responses, such as motions and added resistance in waves, exhibit dependencies on wave steepness. In this paper, the main focus of such uncertainty analyses is on the systematic grid convergence study.