Here we propose two types of customized features to predict the C Q of the EFG tensor: structural features, and elemental features. Structure features are extracted from the local geometries of the materialswithout taking into consideration any difference between atomic species. Significant research in solid-state Al NMR of aluminum-containing materials has focused on the empirical correlation between NMR measurable parameters such as C Q and simple descriptive parameters derived from local geometry . It appears that many of these empirical correlations are particularly useful for the recent efforts of building computational predictive models for NMR spectroscopy. For example, Ghose and Tsang 63 defined the longitudinal strain and the shear strain to quantify the distortion of the local polyhedron from the Platonic solid-like forms (i.e., with identical faces of the geometric solid). Later Baur et al. We implemented the DI parameter in python along with eight simple statistics of local polyhedron geometry: namely maximum, minimum, standard deviation and mean of the first-order bond lengths (fbl) and bond angles (fba). A full list of structural features and their corresponding abbreviations can be found in Supporting Information Table . Figure shows a correlation "heat map" between DFT calculated NMR parameter C Q and the structural features (More details on feature importance can be found in the Supporting Information). The standard deviation of the first-order bond length std(fbl) has a high level of correlation with C Q , which illustrates the power of such simple features when used for the right target. The distortion index (DI) has the secondlargest correlation with C Q . The std(fbl) and DI characterize the distortion of the local polyhedron from its "ideal form" in terms of bond length and bond angle, respectively. We found these two features are complementary to each other in the prediction of C Q . More details about this result can be found in the Supporting Information.