Using Predictive Analytics to Identify Early Warning Signs

In our work, timing is everything. The sooner we identify students who need additional support, the greater the chances of helping them stay on track and thrive.

That’s where predictive analytics becomes a game-changer.

Predictive analytics is more than just a buzzword—it’s a powerful strategy that uses historical data to anticipate potential challenges. For schools, this means identifying students who may need extra support before they show signs of falling behind. It’s about being proactive instead of reactive, and it’s one of the most effective ways school leaders can make a meaningful difference.

Predictive analytics analyzes past and current data—grades, test scores, attendance, behavior, and more—to forecast future outcomes. It helps answer questions such as:

• Who may need attendance, academic or social-emotional support in the coming term?

• Are there students showing signs that they might struggle with certain content?

• Which students are trending away from on-time graduation, and why?

By surfacing early indicators of need, predictive analytics helps schools provide timely, personalized interventions that improve student success.

Key Components of a Predictive Analytics System

1. Historical Data

Effective forecasting draws from multiple years of student data:

• Report card grades and GPA trends

• Attendance patterns

• Discipline referrals and suspension data

• State and district assessment scores

• Credit accumulation and course performance

2. Indicators of Emerging Needs

Use your data to define meaningful indicators that suggest a student may benefit from extra attention. These might include:

• Chronic absenteeism

• Drops in academic performance

• Repeated behavioral referrals

• Incomplete assignments or missed coursework

3. Forecasting Models

Whether developed in-house or through edtech platforms such as ours, predictive models look for patterns that signal a student might face future academic challenges. These models help prioritize support without relying solely on a single test score or grade.

4. Early Support Systems

An early support system (sometimes called an “early warning system”) monitors these indicators and alerts school staff when students are showing signs that they may need additional help. These alerts help ensure students receive support at the right time—before the situation becomes dire.

Why School Leaders Should Pay Attention

• Proactive Interventions: Identify student needs before they become urgent.

• Equity in Action: Ensure every learner gets the opportunity to thrive, especially those who may otherwise go unnoticed.

• Efficient Resource Use: Focus time, programs, and personnel where they’ll make the greatest impact.

• Higher Student Engagement: Students who feel seen and supported are more likely to stay engaged in their learning.

• Better Outcomes: From course pass rates to graduation, students benefit when schools act early.

Example: Imagine discovering that students who miss more than 10% of school days in 9th grade are much less likely to be on track for graduation by the end of 10th grade. With that insight, you can set up a system that flags students approaching that attendance threshold. Teachers and counselors can reach out early, understand the root causes, and provide personalized support—before the student slips off track.

Predictive analytics doesn’t replace the role of teachers and leaders—it enhances it. With the right data and systems in place, schools can better meet each student’s unique needs before those needs grow into barriers.

This approach fosters a culture of responsiveness, care, and equity—where students are seen for their potential, not just their performance.

The American Institute for Research and WestEd created a report on how to create early warning indicators  in schools.