Preclinical studies, along with Phase I, II, and III clinical trials demonstrate the pharmacokinetics, pharmacodynamics, safety and efficacy of a new drug under well controlled circumstances in relatively homogeneous populations. However, these types of studies generally do not answer important questions about variability in specific factors that predict pharmacokinetic and pharmacodynamic (PKPD) activity, in turn affecting safety and efficacy. Semi-physiological and clinical PKPD modeling and simulation offer the possibility of utilizing data obtained in the laboratory and the clinic to make accurate characterizations and predictions of PKPD activity in the target population, based on variability in predictive factors. Capecitabine is an orally administered pro-drug of 5-fluorouracil (5-FU), designed to exploit tissue-specific differences in metabolic enzyme activities in order to enhance efficacy and safety. It undergoes extensive metabolism in multiple physiologic compartments, and presents particular challenges for predicting pharmacokinetic and pharmacodynamic activity in humans. Clinical and physiologically based pharmacokinetic (PBPK) and pharmacodynamic models were developed to characterize the activity of capecitabine and its metabolites, and the clinical consequences under varying physiological conditions such as creatinine clearance or activity of key metabolic enzymes. The results of the modeling investigations were consistent with capecitabine's rational design as a triple pro-drug of 5-FU. This paper reviews and discusses the PKPD and PBPK modeling approaches used in capecitabine development to provide a more thorough understanding of what the key predictors of its PBPK activity are, and how variability in these predictors may affect its PKPD, and ultimately, clinical outcomes.