With advances in computational techniques, numerical methods such as finite element method (FEM) are gaining much of the popularity for analysis as these substitute the expensive trial and error experimental techniques to a great extent. Consequently, selection of suitable material models and determination of precise material model constants are one of the prime concerns in FEM. This paper presents a methodology to determine the Johnson-Cook constitutive equation constants (JC constants) of 97 W Tungsten heavy alloys (WHAs) under high strain rate conditions using machining tests in conjunction with Oxley’s predictive model and particle swarm optimization (PSO) algorithm. Currently, availability of the high strain rate data for 97 WHA are limited and consequently, JC constants for the same are not readily available. The overall methodology includes determination of three sets of JC constants, namely, M1 and M2 from the Split-Hopkinson pressure bar (SHPB) test data available in literature by using conventional optimization technique and artificial bee colony (ABC) algorithm, respectively. However, M3 is determined from machining tests using inverse identification method. To validate the identified JC constants, machining outputs (cutting forces, temperature, and shear strain) are predicted using finite element (FE) model by considering M1, M2, and M3 as input under different cutting conditions and then validated with corresponding experimental values. The predicted outputs obtained using JC constants M3 closely matched with that of the experimental ones with error percentage well within 10%.