Mesoporous silica are promising bio-enabling carriers for poorly soluble drugs. However, a comprehensive understanding of drug-silica interactions and their impact on drug release remains limited. Apart from urgently needed experimental tools, predictive in silico tools that consider drug-carrier interactions in aqueous media are currently lacking. To address this gap, a novel in silico approach (silica-water partitioning coefficient) was introduced in this study. A series of ten drugs were loaded onto a mesoporous carrier (Parteck® SLC 500), and the products were analyzed using differential scanning calorimetry (DSC) and X-ray powder diffraction (XRPD). In vitro dissolution (USP II) profiles of drug-loaded formulations were analyzed and correlated with a newly introduced silica-water partitioning coefficient derived from chemical potential calculations using the Conductor-like Screening Model for Real Solvents (COSMO-RS). Strong correlations were observed between dissolution parameters, such as the initial release slopes (Pearson r = -0.98; p = < 0.05) and AUC values (Pearson r = -0.79; p < 0.05), and the calculated chemical potential-based partitioning coefficient. This study introduces a predictive method based on COSMO-RS-derived chemical potentials to estimate silica-water partitioning for drugs, thereby predicting their release performance from mesoporous silica formulations. The results demonstrate that these calculated chemical potentials can qualitatively rank the drug release kinetics in aqueous media. Further investigation with additional compounds and carrier types may broaden the applicability of this approach as a mechanistic tool for mesoporous silica formulation development and contribute to narrowing the gap toward future clinical translation.