In this work, we developed random forest models that predict the maximum oscillator strength and corresponding excitation energy of a molecule. Our models trained with almost one million DFT results yielded highly accurate predictions. In addition to the high prediction accuracy compared to the existing prediction models, this study presents its importance at one of the few theoretical studies on the prediction of the oscillator strength of a molecule. We further identified molecular fragments and molecular descriptors important for determining the oscillator strength of a molecule. We believe that these findings will serve as a useful guideline for the design of novel fluorophores.