The paper presents a model-based approach to diagnostic reasoning in medicine. A process model is defined on the levels of static elements, dynamic elements and reasoning control. Static elements, facts, hypotheses and different types of disease knowledge, are identified and variations relevant for hypotheses generation are described. Dynamic elements correspond to actions, which in turn modify static elements, but are also controlled and started by the expressions of the static elements. Hypothesis generation starts with the assessment of a given set of facts. According to their priorities, facts are used for the construction of a diagnostic differential: new hypotheses are considered, existing hypothesis refined or excluded. The purpose of hypotheses generation is to establish a complete diagnostic differential with disjunctive explanations which explain a given set of facts. The presented model could serve as a basis for an implementation in a model-based and process-oriented decision-support system.