The previous publication assessed how the performance of a RF model is related to the Dice similarity of fluorine fingerprints in a test set to the training set. A RF model was trained on the LEF4000, with or without tranche 1, and used to predict tranche 2. It yielded good predictions of the 19 F NMR chemical shift for those molecules with at least one close analog of a Dice similarity greater than 0.7 in the training set. We here report the performance of predicting tranche 2 after training with the LEF4000 with or without tranche 1 as a function of substructural features present in the fluorine fingerprints.