Aqueous solubility is a key physicochemical property with significant implications in drug discovery, environmental chemistry, and the development of energy materials. Solubility plays a crucial role in drug absorption and can be a determining factor for oral bioavailability and the screening of potential drug candidates . To distinguish between compounds with low or high solubility , a large number of experimental assays are typically conducted on various potential compounds. However, these empirical solubility tests are costly, highlighting the need for faster and more cost-effective alternatives during the early stages of drug discovery . In response to this demand, numerous computational methods have been developed to complement or, in some cases, replace traditional experimental assays. Among the various computational modeling, data-driven approaches are now one of the most pursued . These statistical models utilize experimental data to establish a relationship between solubility and a suitable computational representation of the molecule.