In the pharmaceutical industry, solvents account for approximately 80-90% of total material ‎consumption. Selecting the optimum solvent and its binary or ternary mixtures in laboratory ‎experiments requires considerable time and cost. Therefore, the use of semi predictive ‎thermodynamic models can overcome these limitations. In this study, the UNIQUAC SAC ‎activity coefficient model, which is a segment based thermodynamic model, was employed to ‎model the solubility of 123 solid pharmaceutical and non pharmaceutical compounds. First, ‎using reported experimental solubility data, the contribution of conceptual segments for each ‎compound was determined through optimization. These segments were then used to identify ‎the solvent that provides the highest solubility. The obtained results show that the ‎UNIQUAC SAC model is a practical thermodynamic model that can be effectively used in ‎the conceptual design stage of pharmaceutical processes for selecting the optimum solvent.‎