Personalized learning presents both opportunities and challenges in the domain of mathematics. In this chapter, we consider approaches to personalization, distinguishing between personalization focused on learning and motivation goals. We present a framework for thinking about the impact of personalization and provide some practical guidance for developing personalized learning in the domain of mathematics. Our framework considers personalization based on prior and developing knowledge to select tasks or problems in adaptive mathematics software as well as personalization to promote students’ interest, autonomy, and choice as they work with content in such software. Examples are drawn from Carnegie Learning's MATHia, an intelligent tutoring system that is used by hundreds of thousands of learners across the United States every year as a part of their middle school and high school mathematics instruction.