Reasoning with hypothetical cases helps decision-makers evaluate alternate hypotheses for deciding a case. The hypotheticals demonstrate the sensitivity of a hypothesis to apparently small factual differences that may require different results because they shift the tradeoffs among conflicting underlying principles. By anticipating variations, the decision-maker seeks to formulate as general and robust a hypothesis as possible. This paper presents a model of the role of hypothetical cases in assessing legal hypotheses and illustrates it with examples drawn from a Supreme Court oral argument. It describes the LARGO program, an intelligent tutoring system to help law students learn the model by graphically representing complex argument examples. LARGO analyzes students’ graphs and provides feedback to encourage them to reflect on the examples in light of the model.