This article explores decision trees pivotal role in healthcare covering their significance applications and challenges. It outlines their multi-faceted application in medical diagnosis, treatment prediction, and clinical decision support systems, highlighting their capability to derive meaningful insights from medical data for informed decision-making. This paper also considers issues of applying decision trees in healthcare, elaborating on breakthroughs such as advanced algorithms and better data quality to confront these challenges as well as the ethical issues associated with their application in healthcare are brought to light. In conclusion, this review addresses future directions, such as incorporating advanced machine learning methods and investigating ethical considerations, and it also investigates possible synergies between decision trees and future technologies for a more comprehensive healthcare system.