Student-facing learning analytics (SFLA) hold promise for supporting the development of self-regulated learning (SRL) skills students need for academic success, especially in online learning. However, the promise of SFLA for supporting SRL is unrealized because current SFLA design methods are techno-centric, with little attention to learning science theory and student needs, and there is little guidance for SFLA designers. Based on insights from literature and a survey with learning analytics (LA) experts, the authors have developed a framework to guide the design of SFLA. The framework is built around three questions that designers should address to generate SFLA features for supporting SRL: What are the students' self-regulated learning support needs based on self-regulated learning theory; What are the students' perspectives of student-facing learning analytics in meeting their SRL needs? What student-facing learning analytics features are appropriate to support students' self-regulated learning based on their SRL needs? A set of activities that should be conducted to respond to each question is identified within the framework. To evaluate the framework, a focus group discussion with LA experts was conducted, and feedback obtained was used to revise the framework. The framework provides a rationale for understanding student needs as informed by theory.