This research proposes a novel Retrofit Design Approach based on process simulation and the Response Surface Methodology (RSM). The approach comprises a diagnosis stage to select the, promising variables through a sensitivity analysis, an evaluation stage to assess the impact of the promising variables, and to identify the most important factors through RSM. A reduced model from the process response behavior is built, and an optimization is carried out with the reduced model to identify optimal conditions and performance of the system, subject to objective function and model constraints. All these procedures are simulation-supported. The main advantage of the proposed approach is to handle a large industrial-scale design problem within a reasonable computational effort and to obtain a reduced model based on the most important factors Limitations for the developed method include that the global optimality of the solutions found is not fully guaranteed, while large computational time for simulation may be required when the large number of factors and levels need to be considered, although this is Offset by the reduced optimization time. The proposed Retrofit Design Approach has been applied to the NGL (natural gas liquids) recovery process, in which steady-state process simulation using Aspen Plus TM has been carried out, and complex design interactions existed for retrofit scenarios have been systematically evaluated, leading to optimal strategies for retrofitting through the proposed design method. Both the continuous and discrete design options are considered in the retrofit design, and the results showed that the approach is effective to provide reliable, cost-effective solutions which yield to economic and environmental improvements in the studied processes. The promising sets of retrofit design options were presented as a portfolio of investment opportunities for supporting further decision-making procedures.