Among the complex set of features influencing polar cocrystal formation, the HOMO-LUMO energy gap (Eg) was considered as a notable molecular-level parameter, extending beyond conventional understanding in the field. However, its precise role in governing polarity during crystallization remains elusive, necessitating further investigation. The feature B_HOMO_LUMO, representing the Eg of molecule B, exhibited a clear negative correlation with polar cocrystal formation when its value was high. This finding suggests that molecules with smaller Eg are more likely to participate in the formation of polar cocrystals. As such, Eg offers a valuable criterion for guiding molecular design and cocrystal discovery. To refine this approach, we analyzed the distribution of HOMO-LUMO energy gaps for B molecules within our CA-based dataset (see Supplementary Figure ) and identified a threshold of Eg <4.8 eV. Molecules with Eg values below this threshold were identified as promising candidates for polar cocrystal formation with CA. However, it is important to emphasize that this criterion serves as a probabilistic filter rather than a definitive determinant of polar cocrystal formation. While the Eg threshold provides a useful 10 guideline for narrowing down potential candidates and offers an effective pathway for molecular selection, it cannot guarantee success in all cases. The process of cocrystal formation is influenced by a multitude of factors beyond Eg, including molecular packing, intermolecular interactions, and environmental conditions such as temperature, solvent, and concentration. Additionally, proton transfer during cocrystal formation introduces further complexity, as it can alter molecular properties, including dipole moment and Eg, thereby making the molecular-level features as important impact factors to the likelihood of forming polar cocrystals. Such changes in electronic structure emphasize the need for careful consideration of proton transfer effects in predictive models. To address these challenges and improve the predictive power of Eg-based criteria, additional strategies are necessary.