Orally dosed drugs must dissolve in the gastrointestinal (GI) tract before being absorbed through the epithelial cell membrane. In vivo drug dissolution depends on the GI tract's physiological conditions such as pH, residence time, luminal buffers, intestinal motility, and transit and drug properties under fed and fasting conditions (Paixão, P. et al. Mol. Pharm.2018 and Bermejo, et al. M. Mol. Pharm.2018). The dissolution of an ionizable drug may benefit from manipulating in vivo variables such as the environmental pH using pH-modifying agents incorporated into the dosage form. A successful example is the use of such agents for dissolution enhancement of BCS class IIb (high-permeability, low-solubility, and weak base) drugs under high gastric pH due to the disease conditions or by co-administration of acid-reducing agents (i.e., proton pump inhibitors, H2-antagonists, and antacids). This study provides a rational approach for selecting pH modifiers to improve monobasic and dibasic drug compounds' dissolution rate and extent under high-gastric pH dissolution conditions, since the oral absorption of BCS class II drugs can be limited by either the solubility or the dissolution rate depending on the initial dose number. Betaine chloride, fumaric acid, and tartaric acid are examples of promising pH modifiers that can be included in oral dosage forms to enhance the rate and extent of monobasic and dibasic drug formulations. However, selection of a suitable pH modifier is dependent on the drug properties (e.g., solubility and pKa) and its interplay with the pH modifier pKa or pKas. As an example of this complex interaction, for basic drugs with high pKa and intrinsic solubility values and large doses, a polyprotic pH modifier can be expected to outperform a monoacid pH modifier. We have developed a hierarchical mass transport model to predict drug dissolution of formulations under varying pH conditions including high gastric pH. This model considers the effect of physical and chemical properties of the drug and pH modifiers such as pKa, solubility, and particle size distribution. This model also considers the impact of physiological conditions such as stomach emptying rate, stomach acid and buffer secretion, residence time in the GI tract, and aqueous luminal volume on drug dissolution. The predictions from this model are directly applicable to in vitro multi-compartment dissolution vessels and are validated by in vitro experiments in the gastrointestinal simulator. This model's predictions can serve as a potential data source to predict plasma concentrations for formulations containing pH modifiers administered under the high-gastric pH conditions. This analysis provides an improved formulation design procedure using pH modifiers by minimizing the experimental iterations under both in vitro and in vivo conditions.