Use Machine Learning To Predict Court First Instance in Saudi Law by Analysis the Judicial

Predicting the type of Saudi court is helpful for illegal people to know which court is suitable for filing proceedings. However, it isn’t very easy to expect judicial courts in Saudi law because they need a data set of cases. This requires the extraction of valuable information from countless other cases and documents. Moreover, the complexity of Saudi law, coupled with a large volume of litigation, makes this problem more difficult to predict. This paper presents the predictions of the courts of the first instance in Saudi law where the user writes the text of the case to be analyzed and then predicts the type of court suitable for this case. Our methodology uses machine learning algorithms. The prototype obtained 98.36% accuracy using the xgboost algorithm, which was applied to 607 diverse judges in cases of the General Court and the Criminal Court out of five trial courts in Saudi law.