Mango is one of the most economically significant fruit crops worldwide, providing nutrition and livelihood to millions of people. However, mango leaf diseases can cause substantial yield losses and affect the quality of fruits. The most efficient therapy and prevention of many disorders depend on their early identification and precise diagnosis. The purpose of this study is to offer a synopsis of the many approaches used to identify mango leaf diseases. Traditional approaches, such as visual inspection and manual identification, have limitations in terms of accuracy and efficiency. Therefore, researchers have explored alternative methods that utilize advancements in technology and image processing algorithms to automate the detection process