We have developed a stochastic representation of the pharmacologic treatment of hypertension that is useful in predicting the outcome of various therapy protocols (sequences of antihypertension agents). Important variables (compliance, pharmacologic potency, incidence of side effects, symptoms from hypertension, and financial cost) are incorporated in the model, realistically representing the complex interactions involved in the treatment of hypertension from the perspectives of both physicians and patients. The outcome measures of the model are clinically relevant and easily interpreted. The model's predictions were found to conform with data from an empirical study. This treatment model was also used to compare commonly utilized antihypertensive agents within the traditional stepped care approach currently popular among clinicians.health care: treatment, probability: stochastic model applications