Abstract: Addressing the challenges of temperature control and the inadequate precision of conventional heat transfer models in γ-TiAl alloy machining, this study establishes a temperature-pressure dependent heat transfer coefficient prediction model that incorporates the variable thermophysical properties of supercritical CO₂（scCO₂）.Through the implementation of a modified Martin correlation incorporating density and viscosity ratio corrections, we achieved precise calculations of local heat transfer coefficients during the cutting process. A two-dimensional thermo-mechanical coupled cutting finite element model was established based on the ABAQUS platform. The study systematically investigated the influence of cutting speeds ranging from 60 to 180 m/min on temperature field evolution and material removal mechanisms. Our findings demonstrate that the proposed heat transfer coefficient calculation methodology effectively predicts the cooling performance of scCO₂, providing theoretical foundations for optimizing high-efficiency machining processes of γ-TiAl alloys.