A 3rd generation CALPHAD description for pure Mo is presented, with several approaches explored and the final optimized model parameters provided. The lattice stabilities of Mo are critically reviewed, and the inflectiondetection method is recommended for their estimation. Ab initio data are employed to train a machine learning potential, which is then used to support the determination of the instability temperature and the modelling of the liquid phase. The thermodynamic properties of the various phases are successfully described, demonstrating an overall good agreement with the experimental data, even at low temperatures. The unique characteristics of Mo, including significant electronic and anharmonic contributions, are addressed during the modelling. The Equal Entropy Criterion (EEC) is adopted to avoid solid phase stabilization above the melting point. Each modelling choice is thoughtfully discussed and analysed, providing a comprehensive overview of the current best practice for 3rd generation CALPHAD modelling of pure high-melting elements like Mo.