An Anticipatory Framework for Categorizing Nigerian Supreme Court Rulings

It is important to recognize that a well-run judicial system contributes to the formation of a favorable atmosphere that fosters national growth. The efficient administration of justice is just as important to the court's efficacy as its capacity to be impartial, firm, and fair at all times. Notwithstanding these vital functions of the court, Nigeria's legal system is sometimes unsatisfactory and sluggish moving. People no longer trust the courts because of this, as most people think that justice postponed is justice denied. In recent times, machine learning methods have been used for predictive purposes in several domains. In this work, the authors used 5585 records of precedent rulings from the Supreme Court of Nigeria (SCN) between 1962 and 2022 to construct a prediction model for the categorization of judgments. Primsol Law Pavilion, an independently owned data repository, provided the data. Following data annotation and feature extraction, three classification methods (decision tree, multi-layer perceptron, and kNN) were used to construct the model.