Predictive analytics is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. It is used in a variety of fields to make predictions about future events. Some common use cases of predictive analytics include:

1. Fraud detection: Predictive analytics can be used to identify unusual patterns of behavior that may indicate fraudulent activity.

2. Customer churn prediction: Predictive analytics can help businesses identify customers who are at risk of leaving, so they can take action to retain them.

3. Marketing campaign optimization: Predictive analytics can be used to identify the most effective marketing campaigns and target them to the right customers.

4. Supply chain optimization: Predictive analytics can help businesses forecast demand for their products and optimize their supply chain to meet that demand.

5. Predictive maintenance: Predictive analytics can be used to identify equipment failures before they occur, allowing businesses to schedule maintenance before problems arise.

6. Financial risk assessment: Predictive analytics can be used to identify financial risks and mitigate them before they become major problems.

7. Healthcare: Predictive analytics can be used to identify patients at risk of certain conditions, allowing for early intervention and prevention.

8. Climate prediction: Predictive analytics can be used to forecast weather patterns and the likelihood of natural disasters.

These are just a few examples of the many ways in which predictive analytics can be used.