This study investigates the role of turbulent-chemistry interaction in CFD simulations of diesel spray combustion phenomena after end-of-injection (EOI). Recent experimental and computational studies have shown that the spray flame dynamics and mixture formation after EOI are governed by highly turbulent entrainment, coupled with rapid evolution of the thermo-chemical state of the mixture field.. A few studies have shown that after EOI, mixtures between the nozzle and the lifted diffusion flame can ignite and appear to propagate back towards the injector nozzle via an auto-ignition reaction sequence under sufficiently reactive ; referred to as “combustion recession”. Because combustion recession is a highly-coupled transient turbulent-chemistry phenomenon, questions remain regarding the role of non-linear coupling between turbulent mixing and reactive scalars on observed combustion outcomes. In this study, CFD simulations of combustion recession in diesel spray flames are executed to explore this topic. The Representative Interaction Flamelet (RIF) model is employed to account for the non-uniformity of reactive scalars in a computational cell. The results are compared with the laminar based chemistry model, i.e. well-stirred reactor approach. Both simulations are performed using theReynolds-Averaged Navier-Stokes (RANS) framework, such that all the resolved quantities are characterized by ensemble average variables. Since both chemical modeling methods employ detailed chemical mechanisms, the comparison enables us to explain the effects of turbulent-mixing induced spray flame evolution and the dynamics of combustion recession separately. The results from both approaches are first validated against experimental measurements of ignition delay time and flame lift-off length. Then, further examinations of post-spray flame tracking reveal the significant role of flamelet modeling in capturing combustion recession. This comparison suggests that the truncation of high order non-linear terms in mean reaction rate modeling may lead to unrealistic predictions of combustion recession.