In the recent developments, AI/ML is mostly explored in the structural health monitoring of the aero structure. Owing to the complexity and safety of human life AI tool is not explored as main stream design philosophy in the aircraft industry. Aero space structures are Semi-monocoque aircraft structures which are basically consists of thin sheet of metal or composite and stiffeners. Thereby it is quite efficient to transfer the load without much weight penalty. Present study aims to find the no. of horizontal stiffener and vertical stiffener for designing a fuselage frame having certain thickness with no design constraint violated when subjected to load. In the above stated scenario, four design variable and two design constrained are considered. The design variables are the no horizontal stiffeners, no. of vertical stiffener, thickness of the sheet, and elastic modulus of the material. The main aspect of this population based approach is the availability of pool of solutions. FEM simulations were carried out to generate the design solution pool. ANN model is implemented for DL model preparation. The developed Deep learning model will enable the designers to predict the amount of load a frame can withstand for given set of design variable in vary short span of computational time with minimum cost.