Educational institutions are increasingly turning to learning analytics to identify and intervene with students at risk of underperformance or discontinuation. However, the extent to which the current evidence base supports this investment is currently unclear, and particularly so in relation to the effectiveness of interventions based on predictive models. The aim of the present paper was to conduct a systematic review and quality assessment of studies on the use of learning analytics in higher education, focusing specifically on intervention studies. Search terms identified 689 papers, but only 11 studies evaluated the effectiveness of interventions based on learning analytics. These studies highlighted the potential of such interventions, but the general quality of the research was moderate, and left several important questions unanswered. The key recommendation based on this review is that more research into the implementation and evaluation of scientifically driven learning analytics is needed to build a solid evidence base for the feasibility, effectiveness and generalizability of such interventions. This is particularly relevant when considering the increasing tendency of educational institutions around the world to implement learning analytics interventions with only little evidence of their effectiveness.