This study presents a combined experimental and numerical investigation of jet–crossflow interaction relevant to gas turbine blade film cooling applications. Four staggered rows of cylindrical cooling jets inclined at 30° are examined on a flat plate subjected to an incompressible crossflow with a mainstream velocity of 2 m·s⁻¹. Experiments were conducted at a fixed blowing ratio of M = 2 using Particle Image Velocimetry (PIV) to obtain time-averaged velocity fields and turbulence quantities across six measurement planes. Corresponding Reynolds-Averaged Navier–Stokes (RANS) simulations were performed using the standard k–ε and Shear Stress Transport (SST) turbulence models under identical boundary conditions. Quantitative comparisons of normalized axial and vertical velocity profiles (U/Ue and V/Ue) reveal that both turbulence models overpredict near-wall axial velocities in the jet exit region; however, the SST model shows consistently closer agreement with PIV measurements across streamwise locations ranging from X/D = −2 to X/D = 30. In the near-field region, the SST model captures jet penetration and mixing trends more accurately, whereas the k–ε model underestimates jet diffusion and lateral spreading downstream. Turbulent kinetic energy distributions further demonstrate that the SST model provides improved prediction of shear-layer turbulence intensity, although both models underestimate the spatial extent of turbulence compared to experimental data. The results indicate that, under the investigated conditions (M = 2, α = 30°), the SST model offers superior predictive capability for jet–crossflow interaction compared to the standard k–ε model, particularly in regions dominated by strong shear and recirculation. These findings guide RANS turbulence model selection.