Machine learning models are getting scary good at predicting player behavior. Using just 7 days of gameplay data, we can predict 30-day churn with 75-85% accuracy. The most predictive signals aren't always what you'd expect: declining session frequency matters more than declining session length, and social disconnection (reduced friend interactions) predicts churn better than any gameplay metric. Players who stop responding to push notifications are 4x more likely to churn within two weeks. Interestingly, spending money is NOT a reliable retention indicator - some whales churn quickly after large purchases. The real challenge is turning predictions into action: automated intervention systems can reduce predicted churn by 15-30%, but timing and personalization are everything. What predictive models are you running? Have you built churn prevention workflows based on analytics?