Legal Judgement Prediction: A comparative analysis of legal documents in Brazil

Legal Judgement Prediction has become an essential task in several domains of law. It plays a significant role when studies are performed for a given case to assist lawyers and experts. Machine learning approaches have been extensively used among the methods employed to perform this task due to their flexibility and accuracy. However, machine learning methods alone can not be used directly in the raw data, which raises the need for preprocessing and feature engineering methodologies. Several features can influence the final decision on a case. Thus, a comparative analysis of prediction methods and preprocessing strategies was conducted on legal datasets in the Portuguese language. The results showed that ensemble methods achieved the best results in predicting legal cases, achieving an accuracy between 65% and 85% in the data.