An automatic simultaneous identification method for the friction coefficient and heat transfer coefficient is proposed for accurate hot forging process simulation. We established an autopilot finite element analysis system (autopilot FEA; APFEA) that repeats the FEA of the hot ring compression test, minimizing the errors, defined by the compression load and minimum inner diameter reduction ratio, between results of the experiment and the FEA with a machine-learningbased optimization algorithm. The automatic generation of a surface-pressure-dependent friction coefficient function, the selection of the friction law from Coulomb’s and shear friction lows, and the automatic simultaneous identification of the sigmoid curve friction and heat transfer coefficient functions are performed using the APFEA system and the results of a hot ring compression test performed with a quasi-air-suspended heating tester designed by us. As a result, the optimized friction and heat transfer parameters are identified, and the reasonableness of the friction law is evaluated.