Predictive analytics refers to the use of historical and real-time data, statistical models, and machine learning techniques to identify patterns and forecast the likelihood of future outcomes. In education, predictive analytics analyzes student data—such as enrollment patterns, course performance, engagement indicators, and financial factors—to identify students who may be at risk of falling behind or leaving before completing a credential, allowing institutions to intervene early with targeted support.

In the mid-2020s, several postsecondary institutions began to scale the use of predictive analytics to support student success. This approach produced notable improvements in student outcomes at a group of large “early adopter” public universities, including Georgia State University, Arizona State University, University of South Florida, California State University, Long Beach, and University of Texas at San Antonio. Within roughly a decade, graduation rates across these institutions improved from under 50% to nearly 70%, significantly outpacing gains made by public universities nationally.

Strategies based on predictive analytics leverage data and emerging technologies to improve administrative processes that affect all postsecondary students—registration, advising, student communications, and course scheduling. These approaches use large datasets to support proactive advising and tutoring, design small grant programs that provide emergency financial aid, improve academic and curricular design, and build personalized communication platforms.

While these strategies focus on improving the systems that affect all students, their benefits are often greatest for students who face the most barriers to completion, including low-income students, rural students, part-time students, first-generation students, Black and Hispanic students, and military-affiliated learners.

These approaches can also produce financial benefits for students. By reaching out proactively with analytics-informed interventions and early alerts—and by identifying and addressing academic bottlenecks—institutions have been able to reduce the average time to degree. In doing so, they also help reduce the amount of debt students incur while completing their programs.