In the last decades, research was carried out in the investigation of the effects of paintings on the performance of naval vessels. A large proportion of the publicly available research focused on paints that reduce the fouling and friction coefficient of the hulls of these vessels, such as hydrophobic paints. However, research applied to propellers is scarce. Covering the blade surface with paint exhibiting hydrophobic behavior changes the drag of the blades and, consequently, the torque required by the propeller. However, covering a blade fully can adversely affect the flow in certain regions, reducing the performance of the propeller or inducing cavitation inception. This project studies the distribution pattern of the super-hydrophobic surface (SHS) paint on model-scale propellers using the topology optimization method to determine regions where the application of surface treatment leads to improved propeller performance. Propeller simulations were carried out with full turbulent analysis using Reynolds-Averaged Navier-Stokes equations. The numerical method is developed to model the behavior of the boundary layer with boundary conditions that impose the low friction/hydrophobicity effect to predict the performance of a coated propeller. To obtain the topology optimization sensitivities, the discrete adjoint method of the Navier-Stokes equations with the hydrophobic model based on the slip length is studied. The numerical implementation is done by using the Star-CCM+ as the Computational Fluid Dynamics (CFD) software, based on the Finite Volume Method (FVM) as the primal and the adjoint solver, and Interior Point Optimizer (IPOPT) as the optimizer. Derivation of the discrete adjoint problem applied to super-hydrophobic modeling is shown. The application of topology optimization to the hydrophobic distribution on a two-dimensional cases are demonstrated (using internal and external flow as test cases), and for a threedimensional case (propeller). Despite that the SHS behavior is simplified by adopting the slip length model, the obtained results show that regions to be prioritized in order to reduce the dissipated energy is not always intuitive. Furthermore, depending on the operating condition, a fully-SHS case may not be the best option. The novel application of fluid Topology Optimization can be extended for other applications, such as problems of surface design.