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Transition-metal ions with d3 electronic configuration such as Cr3+ and Mn4+ are utilized as emission centers in various luminescent materials such as ruby (Cr3+-doped -Al2O3) or alexandrite (Cr3+-doped chrysoberyl). Since it is difficult to investigate the multiplet energy levels of Cr3+ in a wide variety of oxide crystals experimentally, the theoretical prediction of the energy of the emission level (2Eg) is indispensable for the efficient development of novel Cr3+-doped luminescent materials. In this study, we predicted the multiplet energy of the emission level (2Eg) of Cr3+ in oxides by first-principles calculations based on the discrete variational multi-electron (DVME) method using relatively small clusters consisting of seven atoms. However, the correlation coefficient between the calculated 2Eg energy and the experimental ones was relatively low (0.52). In order to improve the accuracy of the prediction, we also performed a machine learning modeling. By using the calculated 2Eg energy and the other electronic and structural parameters as the attributes, we created the predictive model of the 2Eg energy of Cr3+ in oxides. The predicted 2Eg energies are in good agreement with the experimental ones, showing a high correlation coefficient of 0.92.