In addition, the use of machine learning has been investigated to search for stable new materials, and there have been many attempts to predict the stability of inorganic compounds using new descriptors such as the Coulomb matrix and the Orbital Field Matrix. However, these simulations and predictions are, in many cases, difficult to handle in a generic and quantitative manner to determine what is contributing to the stability of a compound. Similarly, the importance of computational stability discussions has been recognized in layered intercalation compounds as well, and while there have been searches limited to specific hosts, such as the self-intercalation from calculations in transition metal dichalcogenides (TMDs) and the search for stable graphite intercalation compounds (GICs) we reported, universal factors for the stable host-guest combinations have yet to be extracted.