Predictive analytics is a technique used in artificial intelligence and machine learning to predict the outcome of a future event. This technique involves the use of machine learning algorithms to analyse historical data and create models that can predict how a variable will behave in the future.

Predictive analytics is commonly used in a variety of applications, such as fraud detection, business decision making, process optimisation and prediction of future events. This technique can be useful in situations where a decision needs to be made based on data about a future event, but complete information about the event is not available.

Techniques used in predictive analytics include supervised learning, which involves the use of labelled historical data to train a machine learning model that can predict future outcomes, and unsupervised learning, which involves the use of clustering and association techniques to identify patterns in the data and make predictions based on those patterns.

Predictive analytics can also include the use of statistical models to make predictions and decisions based on the data. These models may be linear or non-linear, and may include techniques such as regression, time series analysis and survival analysis.