In response to the need for more advanced gas turbine cooling design methods that factor in the 3-D flowfield and heat transfer characteristics, this study involves the computational optimization of a pressure side film cooling array on a modern turbine inlet vane. Latin hypersquare sampling, genetic algorithm reproduction, and Reynolds-Averaged Navier Stokes (RANS) computational fluid dynamics (CFD) as an evaluation step are used to assess a total of 1,800 film cooling designs over 13 generations. The process was efficient due to the Leo CFD code\u27s ability to estimate cooling mass flux at surface grid cells using a transpiration boundary condition, eliminating the need for remeshing between designs. The optimization resulted in a unique cooling design relative to the baseline with new injection angles, compound angles, cooling row patterns, hole sizes, a redistribution of cooling holes away from the over-cooled midspan to hot areas near the shroud, and a lower maximum surface temperature. To experimentally confirm relative design trends between the optimized and baseline designs, flat plate infrared thermography assessments were carried out at design flow conditions. Use of flat plate experiments to model vane pressure side cooling was justified through a conjugate heat transfer CFD comparison of the 3-D vane and flat plate which showed similar cooling performance trends at multiple span locations. The optimized flat plate model exhibited lower minimum surface temperatures at multiple span locations compared to the baseline. Overall, this work shows promise of optimizing film cooling to reduce design cycle time and save cooling mass flow in a gas turbine