Epstein (1995) defended the superiority of simple legal rules over complex, human-designed regulations. Has Epstein’s case for simple rules become obsolete with the arrival of artificial intelligence, and in particular machine learning (ML)? Can ML de-liver better algorithmic rules than traditional simple legal rules? This paper argues that the answer to these question is “no.” I will build an argument based on three increasingly more serious barriers that ML faces to develop legal (or quasi-legal) algorithmic rules: data availability, the Lucas’ critique, and incentive compatibility in eliciting information. Thus, the case for simple legal rules is still sound even in a world with ML.