import pandas as pd
from sklearn.ensemble import RandomForestClassifier
def predict_failure(machine_id):
telemetry = pd.read_sql("SELECT * FROM machine_telemetry WHERE machine_id = ?", machine_id)
features = telemetry[['vibration','temperature','runtime_hours','cycle_count']]
model = RandomForestClassifier()
model.fit(features, telemetry['failure_within_30d'])
risk = model.predict_proba(features.iloc[-1:])[0][1]
return 'High' if risk > 0.7 else 'Medium' if risk > 0.4 else 'Low'