This paper explores the application of machine learning (ML) techniques in the diagnosis and prognosis of liver diseases. With the increasing prevalence of liver diseases worldwide, accurate and early diagnosis is critical. Machine learning offers promising tools for enhancing diagnostic accuracy and predicting disease outcomes. This study reviews recent advancements in ML applications for liver disease, discusses various methodologies employed, presents experimental results, and highlights the potential and challenges of ML in clinical practice.