In this day and age, the deficiency of resources for synthetic chemicals and massive challenges for waste carries the circular economy, including re-cycling waste, into focus. Consequently, it would provide waste a value that is one of the most essential incentives for all researchers to take better care and to avoid non-recyclable waste. In fact, the researchers established how computers equipped with wide synthetic knowledge (forward-synthesis with well-known reactions in chemical and related industries) can help to address the chemical waste challenge. In this context, Artificial Intelligence/Machine learning (AI/ML) can automatically learn from data and can perform tasks such as predictions and decision-making. Interdisciplinary studies combining AI/ML with chemical health and safety have demonstrated their unparalleled advantages in identifying trend and prediction assistance, which can greatly save manpower, material resources, and financial resources. In this summary, recent research work of AI/ML in sustainable and cycle chemistry will be introduced.