In sizing a flight control system, one of the main required parameter is the hinge moment. The hinge moment of a control surface is given by the forces acting on the surface itself multiplied by the mechanical transmissions arm. This moment is assumed to be evaluated on the hinge axis, which is generally the only rotating component of an aircraft wing. Due to its high rate of variation depending on flight attitude and conditions, hinge moment boundaries are often numerically evaluated during design phase. The present study aims to introduce a methodology and draft guidelines to collect and analyze a great number of data entry, in order to fill a dataset to be used for building a simple Deep Learning Network (DLN) model.