Film cooling is a very common technique used in cooling turbine engine components, and hence has been studied extensively experimentally and computationally. Computational studies of film cooling range from more simplistic RANS predictions to high fidelity LES predictions. Generally the accuracy of computational predictions of film cooling is evaluated based on the adiabatic effectiveness measured and predicted downstream of the hole. For this study, a RANS computational prediction was used, but the evaluation of the accuracy of the prediction was based on measured thermal and velocity fields within the coolant hole and immediately downstream. We chose a relatively complex film cooling configuration consisting of a row of 7-7-7 shaped holes fed by an internal channel flow with a range of internal crossflow velocities and coolant jet velocities. Previous experimental studies using this configuration showed that at various inlet velocity ratios, the coolant jet becomes biased to one side of the diffusing section of the hole, which degrades performance and can cause ingestion into the hole. For this study we wanted to determine the capability of a RANS computation to correctly predict the flow structures, coolant jet biasing, and film effectiveness for this configuration. Computational results were compared to thermal field measurements made with a micro-thermocouple probe, velocity field measurements made with a PIV, and film effectiveness measurements made with an IR camera. These measurements were made within the coolant hole, at the downstream edge of the hole, and at 5D downstream of the hole. Results from this study show that the RANS computations accurately predicted the bulk flow and thermal fields within and at the downstream edge of the hole, but failed to predict the evolutions of the thermal field, secondary flows, and film effectiveness downstream of the hole.