High-temperature heat pumps (HTHPs) have gradually begun to play an essential role in using heat in industry for waste heat recovery and providing higher-grade heat. The isentropic efficiency and volumetric efficiency of HTHPs are significantly affected by high-temperature operating conditions, which take the pressure ratio (PR) as the key parameter, with limited consideration of other factors such as temperature. Relying on the experimental data obtained from the industrial-grade HTHP system experimental platform, this work proposed an XGBoost-MLR algorithm-based method to identify the key parameters of HTHP isentropic efficiency and volumetric efficiency. High-precision (R² > 0.95) prediction models were established to determine the effect of temperature variables on isentropic efficiency and volumetric efficiency. After the key parameters were identified, the empirical equation of isentropic efficiency and volumetric efficiency applicable to this operation condition were constructed. The average relative errors of the two empirical formulas were 5.95% and 5.28%, respectively. Finally, the generalizability of empirical formulas was verified using experimental data from other researchers. The isentropic empirical formula had a relative deviation of less than 10% under twin-screw compressor conditions. However, the applicability of the volumetric efficiency empirical formula was unstable in compressors of different sizes. The feasibility of the method was also discussed.