Nowadays, the automotive industry is one of the largest areas of CFD (Computational Fluid Dynamics) simulation applications. The big challenge that engineers dealing with CFD simulations in this industry have to face is shape optimization, which is often very time-consuming and requires a lot of iterations. To reduce the time needed to achieve an optimal shape and make the design process more efficient, more and more CFD analysts are turning to Adjoint Solver (AS) formulas, a new methodology used for optimization in the automotive as well as railway industry. The AS method calculates gradients (directions, quantities) directly by solving conjugate equations, which makes them independent of design variables. The article concerns optimization the shape of the front wing of the racing car in order to obtain the highest possible downforce-to-drag ratio. At the beginning, 2D shape optimization of the front wing was performed. The next stage of work was the preparation of a CAD (3D) model that took into account the change in the shape of the wing, obtained during the optimization process, and then performing a flow analysis for it.