The extensive use of Machine Learning (ML) algorithms has significantly altered decision-making processes, societal structures, and power dynamics. These algorithms, known for their efficiency, are increasingly making critical decisions. However, concerns about their opacity and biases persist. Some legal scholars and data scientists argue that the GDPR includes a right to explanation to address ML opacity, while others advocate for transparency as a better solution. This study explores the debate between transparency and explanation within the GDPR’s regulatory framework, focusing on Articles 15, 22 and recent EU court rulings. By examining judicial developments and scholarly perspectives, the study highlights the GDPR’s efforts to promote transparency and accountability in automated decision-making. Despite the GDPR’s provisions, the lack of an explicit right to explanation has led to ongoing legal and ethical discussions. This research aims to provide insights into how transparency, explanation, and individual rights intersect in the realm of algorithmic decision-making under the GDPR.