Following our previous work , we present a fully automated QM-based workflow that computes C-H hydricities. DMSO was chosen as solvent as most compounds were experimentally measured in that medium. Hydride abstraction is carried out at each unique site by converting a SMILES string into a RDKit molecule object, producing a list of SMILES for each C-H bond. We generate 𝑚𝑖𝑛(1 + 3 * 𝑛 𝑟𝑜𝑡 , 20) conformers for each SMILES using RDKit (v. 2023.09.3) , where (𝑛 𝑟𝑜𝑡 ) represents the number of rotatable bonds. Each conformer undergoes optimization in dimethylsulfoxide (DMSO, 𝜖 = 47.2) using GFN-FF-xTB and the analytical linearized Poisson-Boltzmann (ALPB) as the implicit solvation model. We then remove conformers with relative energies above 3 kcal/mol and select unique conformers by taking the centroids of a Butina clustering using pairwise heavy-atom root mean square deviation (RMSD) with a threshold of 0.5 Å . To identify the lowest energy conformer, we subsequently re-optimize the remaining conformers in DMSO with GFN2-xTB and apply the ALPB implicit solvation model. We then conduct re-optimization in ORCA (v. 5.0.4) , using the composite electronic structure method r 2 SCAN-3c and the conductor-like polarizable continuum model (CPCM) as the implicit solvation model. r 2 SCAN-3c is chosen as the optimal functional based on a benchmark study that evaluates the accuracy of different levels of theory, ranging from semiempirical methods (xTB ), composite electronic structure methods (r 2 SCAN-3c ) to DFT methods (M06-2X , CAM-B3LYP ). All methods are evaluated either as single-point calculations or optimization and frequency calculations. Refer to section 1 in the Supporting Information for more details. Hereafter, we check the geometries for imaginary frequencies and use the total thermal energy at 298.15 K. Following a similar approach from our previous paper for C-H pK a values , we compute the hydricity through the direct hydride transfer reaction, 𝐴𝐻 𝑠𝑜𝑙𝑣 ⇌ 𝐴 + 𝑠𝑜𝑙𝑣 ; see Equation 1.