Abstract: Machine-learning processing of aggregate data including record-size data to predict failure probability is described herein. In an example, a system identifies electronic data that is longitudinal and includes a set of electronic records pertaining to a given subject or to a given object. The system generates a record-size metric that characterizes a size of the electronic data and determines a physical attribute of the given subject or the given object. The system generates a physical-attribute metric based on the physical attribute, generates an input data set that includes the record-size metric and the physical-attribute metric, and generates a failure probability across a given time period and for the given subject or the given object by processing the input data set using a trained machine-learning model. The system determines that an alert condition is satisfied based on the failure probability and outputs an alert representing the failure probability.