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Membrane distillation (MD), a thermally driven phase separation method, has a number of benefits, including the capacity to process a variety of input solutions, high purity and yield of the purified liquid, and minimal energy usage. Applications such as, water treatment, chemical separation, and fuel purification are benefiting from its versatility and scalability. Machine learning (ML)–in demand topic of the last years–is the use of statistical models and algorithms to allow machines to learn and make decisions quickly for humans. In this study, we investigated the use of machine learning in membrane distillation. It was understood that the number of articles in international peer reviewed journals/books was very few (10 documents). Besides most of the documents (6) were published in 2022. We briefly presented what topics the published articles focus on, which ML algorithms they use, and their results. The results showed that the integration of machine learning methods in the field of membrane distillation is open and offers important opportunities to researchers who want to work on this subject.