Multidisciplinary optimization is a highly iterative process that requires a large number of function evaluations to evaluate objective functions and constraints. Metamodels for computationally expensive functions or simulations can be employed in the multidisciplinary optimization instead of the actual solvers resulting in significant computational savings. In this paper, metamodeling is applied to the multidisciplinary design optimization of a ship hull with resistance, seakeeping, and maneuvering performance analyses. At the top system level, a simple cost metric is defined to drive the overall design optimization process. Changes to the hull shape are reflected in the numerical model for resistance computations and in the simulations associated with the seakeeping and maneuvering disciplines. An automated process has been developed for propagating changes to the numerical (CFD) model for the resistance computations; this expedites the computations at the sample points used for developing the metamodels. The validity of employing metamodels instead of the actual solvers during the optimization is demonstrated by comparing the values of the objective functions and constraints at the optimum point when using the actual solvers and when using the metamodels.