This paper proposes an identification methodology based on nanoindentation analysis of coating/substrate system to extract the elastic-plastic properties of coating materials on elastic-plastic substrate when the indenter penetration depth is greater than the film thickness. In order to accurately predict the elastic-plastic properties of the coating materials, a trust-region reflective optimization algorithm is integrated with the finite element analysis, in cooperation with the Jönsson and Hogmark model. The proposed reverse analysis algorithm modifies a predicted load-displacement (P-h) curve by changing the elastic-plastic properties of the coating and the substrate until it fits the experimental nanoindentation (P-h) curve. Numerical and instrumental indentations tests were carried out on a CrN film/Martensitic stainless steel substrate system to verify the proposed reverse method, by which Young's modulus (E), yield stress (σy), and work hardening exponent of the film were obtained. A sensitivity analysis is conducted to study the effect of the elastic-plastic properties of the CrN film/substrate on the (P-h) curve. The results showed a high impact to the loading and unloading part of the (P-h) curve due to variations in (E) and (σy) of the steel substrate compared to those of the CrN coating.