Acute Kidney Injury (AKI) is a common disease consisting in the loss of functionality of the kidneys. Depending on the length of the episode, it can be classified as transient or persistent. Failures lasting longer than 48-72 hours were proved to be related to higher short- and long-term mortality and morbidities. Whereas the recent literature focused on the usage of biomarker tests to predict persistent AKI, the innovation of the proposed approach consists of processing time-series measurements of clinical parameters of the patients and using machine learning algorithms to predict the onset of a persistent renal injury. The patients satisfying the inclusion criteria belonging to the eICU-CRD database were split into training, validation, and test set.