The numerical search for the optimum shape of airfoil/wing geometry is of great interest for aircraft and turbomachinery designers. However the conventional method of design and optimization, which is to repeat the process of modifying airfoil/wing geometry data based on the flow field calculation of initial geometry, is computationally intensive and time-costly. In lieu of this, this article introduces an applicable airfoil/wing inverse design method with the help of Artificial Neural Network and airfoil/wing database, so that a properly trained network should directly provide an airfoil/wing that fits the required aerodynamical features. Repeating the process itself being avoided, the design efficiency improves. This article will present the detail of setting up the airfoil/wing inverse design method and provide the verification of the applicability of the approach.