Abstract: Since a fluid flow model simulation might take a long time computation, even more if it is included a turbulence model, it would be necessary to develop new techniques which could accelerate that computational time. With the Reduced Basis Method (RBM) it is possible to compute a real-time solution of a parametrized partial differential equation (PDE), by using Galerkin projection onto a low-dimension space of basis. This space is properly selected by the Greedy algorithm for which it is necessary a residual-based a posteriori error estimation. In this talk, we present a RBM for the equations which model the fluid dynamics. We present the numerical analysis involved in the construction of the reduced model, and some numerical tests in which we show the speedup for the computation of the solution.