A method is provided for predicting occurrence of a temperature rise event caused by a fire within an environment. The method comprises receiving temperature data captured by at least one temperature sensor 6, 8 for sensing an ambient temperature in the environment, processing the temperature data captured by the at least one temperature sensor in a previous window of time using a trained machine learning model 16 to determine a risk indication indicating risk of the temperature rise event occurring in a future window of time, and outputting a warning indication in dependence on the risk indication determined using the machine learning model. This is useful for providing firefighters with advance warning of dangerous temperature rises such as flashover events.