This research is dedicated to developing an evaluation model for stratigraphic recombination from a micro-level perspective, aimed at enhancing the development strategies for multi-layered reservoir stratigraphic recombination. Utilizing the Lorentz curve and Gini coefficient, the model integrates an unconnected capillary two-phase flow model and accommodates the variability in physical parameters such as permeability and viscosity across different reservoir layers. This approach allows for the simulation and forecasting of the arrival times of the oil–water interfaces at production wells in various sub-layers. Findings from the study indicate that selecting combinations of principal and auxiliary layers based on the differences in physical properties can effectively manage the uniform arrival times of the oil–water interfaces, thus significantly improving development outcomes. The predominant factors influencing stratigraphic recombination are the contrasts in permeability and crude oil viscosity between the principal and auxiliary layers, with more favorable recombination development outcomes achieved when the displacement front equilibrium coefficient is less than 0.28. This research introduces the Gini coefficient and employs a combination of the Lorentz curve with multi-layer fluid dynamics analysis, offering a novel assessment and optimization tool for the recombination of complex multi-layered reservoirs, which holds substantial theoretical value and practical application prospects.