1. A method for predicting failures in an artificial lift system, the method comprising: extracting one or more features from a dataset including time sampled performance of a plurality of artificial lift systems disposed across a plurality of different oil fields, the dataset including data from failed and normally operating artificial lift systems; and forming a learning model based on identified pre-failure signatures in the extracted features, the learning model configured to predict a failure of an artificial lift system based on observation of one of the identified pre-failure signatures in operational data received from the artificial lift system.