Machine Learning

Predictive Risk Scoring

Predict risk before it becomes chronic

3 Weeks
Early Warning Before Chronic Absence

What It Does

Our machine learning model analyzes hundreds of data points to identify students heading toward chronic absenteeism—3 weeks before it happens. By catching students in the "yellow zone" (3-5 absences), schools achieve an 80% intervention success rate compared to just 20% once chronic absence is established.

Research-backed barrier weights (Housing +25, Transport +15)
Yellow zone detection (3-5 absences = 80% intervention success)
Continuous learning from your intervention outcomes

Key Benefits

Everything you need to transform how your school addresses attendance challenges.

Research-Backed Scoring

Risk factors are weighted based on peer-reviewed research on chronic absenteeism predictors.

80% Intervention Success

Catching students in the yellow zone (3-5 absences) dramatically increases intervention effectiveness.

Real-Time Updates

Risk scores update continuously as new attendance and barrier data comes in.

Transparent Factors

See exactly why a student has a high risk score—no black box algorithms.

Historical Trends

View how a student's risk score has changed over time to understand patterns.

Continuous Learning

The model learns from your school's intervention outcomes to improve predictions.

How It Works

Simple, Powerful, Automated

From data to actionable intelligence in just a few steps.

Step 1

Data is collected from SIS and barrier tracking systems

Step 2

ML model analyzes attendance patterns and risk factors

Step 3

Barrier weights are applied (Housing +25, Transport +15, etc.)

Step 4

Yellow zone detection flags students at 3-5 absences

Step 5

Model continuously learns from intervention outcomes

Use Cases

Built for Your Role

See how different team members use this feature in their daily workflow.

1

Data Analyst

Views school-wide risk distribution dashboard to identify systemic issues and allocate resources.

2

Counselor

Reviews individual student risk profiles to understand contributing factors and plan interventions.

3

Principal

Uses trend analysis to identify which barriers are most prevalent and advocate for resources.

Ready to Get Started?

See Risk Prediction in Action

Join hundreds of schools using BrainBridge to transform how they support at-risk students.

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