Accurate numerical prediction of surface heat transfer in the presence of film cooling within aero-engine sub-components, such as blade effusion holes and combustor liners, has long been a goal of the aero-engine industry. It requires accurate simulation of the turbulent mixing and reaction processes between freestream and the cooling flow. In this study, the stress-blended eddy simulation (SBES) turbulence model is used together with the flamelet generated manifold (FGM) combustion model to calculate the surface heat flux upstream and downstream of an effusion cooling hole. The SBES model employs a blending function to automatically switch between Reynolds-averaged Navier–Stokes (RANS) and large eddy simulation (LES) based on the local flow features, and thus significantly reduces the computational cost compared to a full LES simulation. All simulations are run using ansys fluent®, a commercial finite-volume computational fluid dynamics (CFD) solver. The test case corresponds to an experimental rig run at Massachusetts Institute of Technology (MIT), which is essentially a flat plate brushed by a uniform freestream of argon with ethylene seeded inside, and is cooled by either a reacting air or a non-reacting nitrogen jet inclined at 35 deg to the freestream. Calculations are performed for both reacting and non-reacting jet cooling cases across a range of jet-to-stream blowing ratios and compared with the experimental data. The effects of mesh resolution are also investigated. Calculations are also performed across a range of Damköhler number (i.e., flow to chemical time ratio) from zero to 30, with unity blowing ratio, and the differences in the maximum surface heat flux magnitude in the reacting and non-reacting cases at a specific location downstream of the hole are investigated. Results from these analyses show good correlation with the experimental heat flux data upstream and downstream of the cooling hole, including the heat flux augmentation due to local reaction. Results from the Damköhler number sweep also show a good match with the experimental data across the range investigated.