Agent-based modeling is actively used for modeling human health. The main advantages of an agent-based approach in this field are the capability to implement a modular approach to health and to account for individual patient indicators. The article presents the concept of a flexible and expandable agent model of the patient, which performs a long-term prediction of the patient-#039;s condition based on short-term test treatments administered to them, including geroprophylactic, and by predicting the patient-#039;s reaction to exposure in order to prevent future possible diseases with regard to both calendar and biological age. All interactions of the model agents are reduced to assessing the effectiveness of the anti-aging measures in the form of a calculated bio-age which characterizes the degree of decrease in the functional capacity of the organism. As part of the concept, the central agents “Patient”, “Aging Process” and “Impact” are highlighted in the model as well as a number of lower-level agents associated with the agent “Patient”. Lower-level agents are responsible for modeling the physiological processes of body systems or diseases, for example, a chronic disease is allocated its own agent, which affects the patient-#039;s condition during the modeling. The types of model agents are extensible, which makes it possible to develop this concept of the model. The paper presents the testing of the agent model concept to identify the effectiveness of the impact on the patient following on from the assessment of changes in the biological age before and after geroprophylactic therapy.