In summary, we used the PAH101 dataset of GW +BSE calculations to train SISSO models to predict the first singlet excitation energy, which corresponds to the optical gap, the first triplet excitation energy, the singlet-triplet gap, and the singlet exciton binding energy of organic molecular crystals. SISSO models were selected based on considerations of accuracy and computational cost to design materials screening workflows for each property. The screening targets were chosen to demonstrate typical use-cases relevant for organic electronic devices. We demonstrated screening for materials with an optical gap in a particular color; materials meeting the requirements for up-conversion of infrared light to the visible range via TTA, namely, a triplet excitation energy in the infrared, optical gap in the visible range, and a higher TTA driving force than rubrene; materials with a small singlet-triplet gap, which is desirable for OLEDs; and materials with a small singlet exciton binding energy to facilitate the separation of excitons into free charge carriers.