Hydrogen is an energy carrier that presents distinctive opportunities to advance a variety of technologies, due to its notable gravimetric energy density of 120 MJ kg -1 and versatile end uses in combustion, in fuel cells, as a chemical reductant, etc. Currently, most hydrogen is produced from Steam Methane Reforming (SMR), which involves reacting natural gas with steam. Additionally, other fossil fuel-based methods, such as coal gasification, can also be employed to produce hydrogen, as the demand for hydrogen increases. Hydrogen also displays considerable potential for production through renewable energy sources or via the direct mining of natural hydrogen. Regardless of the production method employed, hydrogen is usually generated as a gas at relatively low pressures ranging from 1 to 50 bar, necessitating additional compression for effective storage and transportation. While mechanical compressors, including piston and diaphragm types, are commonly employed, they exhibit limitations such as high operating costs and limited reliability. In addition, the complex designs of most mechanical compressors suffer from hydrogen leakage, produce significant noise during operation, and lead to increased maintenance requirements. New technologies focused on metal hydrides for hydrogen compression are being developed, utilizing the re-versible reaction between metal alloys and hydrogen at various pressures. These compressors offer several advantages, including high discharge pressures of up to 1000 bar H 2 , excellent scalability, and a modular design that allows the use of low-grade thermal energy to enhance energy efficiency. The absence of moving parts simplifies their design, increases reliability, and reduces noise, making them an attractive option for hydrogen compression. Metal alloys based on AB, AB2, or AB5 phases are typically considered as active materials for the development of single-stage and multi-stage hydride compressors. However, as noted by Lototskyy et al. and Yartys et al., only a limited number of interstitial-type metal hydrides possess the necessary reversibility and reaction kinetics to be effective in these applications. In addition, the pressure-composition-temperature (PCT) curves of many alloys proposed for H 2 compression exhibit sloped plateaus and significant absorption-desorption hysteresis, which limits the usable capacity and compression ratio. Furthermore, a priori computational prediction and optimization of metal hydrides for high-pressure hydrogen compression is challenging for a variety of reasons. Compositional machine learning (ML) models for metal hydride thermodynamic properties provide an excellent preliminary screening tool, but highly accurate predictions for ultra-low stability hydrides remain a challenge. This primarily arises due to the imbalance of existing experimental data on which these models are trained, i.e., the extreme lack of experimental data for materials whose hydride plateaus require experimental PCT measurements greater than 100-200 bar. First-principles-based calculations or simulations enabling metal hydride phase equilibrium predictions (i.e., PCT curves), which can themselves be accelerated by various machine-learning approaches, have been proposed as well and can in principle overcome out-of-distribution accuracy issues, but these typically cannot account for sloping plateaus and hysteresis which also substantially impact a metal hydride's compression performance; therefore, experimental validation is required anyway, requiring highly specialized experimental equipment for accurate PCT measurements up to 1000 bar.