Incorporating domain knowledge into the machine learning model selection process involves identifying and selecting relevant features, defining appropriate evaluation metrics, and selecting the most appropriate models based on prior knowledge of the problem domain. This can be achieved through collaboration with domain experts, performing exploratory data analysis, and applying techniques such as feature engineering to create relevant features.