Rank correlations have been used to test independence between pairs of variables, but extending this to multiple variables has been a challenge. This paper introduces a new method called center-outward ranks and signs to create consistent and distribution-free tests of independence for random vectors. By using this method, researchers were able to develop tests that are not only reliable but also statistically efficient. The approach allows for direct calculation of null distributions and shows significant power in detecting differences between variables.