Reinforced Concrete (RC) structures frequently need restoring or potentially strengthening, because of a difference in use, growing or disintegration of materials delivered by natural components, or material damage because of unexpected loads. One fundamental implementation of this retrofitting modernism with fiber sheets to give external detention to RC structures when the limit of the existing structure is inadequate. In this paper, we present a novel experimental examination dependent on retrofitting reinforced concrete beams with regular hybrid fibers comprising of sisal and coir fiber. The concrete was blended with specific design ratio dependent on the evaluation of M20, M25, M30, and M35 grades. The specimens are cast and restored before testing. The behavior of the beams is inspected with the assistance of deflection, ductility, Load Carrying Capacity (LCC), and Energy Absorption Capacity (EAC). The experimental outcomes were investigated with simulation modeling that has been completed to simulate the behavior of the considerable number of beams. For validation purpose, we have utilized Artificial Neural Network (ANN) with structure optimization process. The optimal result is finding out by comparing the retrofitted specimen into control specimens. The result found that hybrid fiber retrofitted specimen performs low deflection and ductility at high loads and then increase the LCC and EAC compared to Control beams (CB1 and CB2). The soft computing strategies decrease computational time and limit the expense in a compelling way.