Multi-View Modeling Framework for ML Systems (M$^3$S) provides a framework to synchronize the experimental nature of machine learning and the deterministic side of traditional software engineering. However, understanding the framework’s generality and limitation still require further investigation. This paper compares the existing validation case study to a new case study of the OCT image diagnosis support system. The comparison between the two case studies shows M$^3$S capability to handle variations in the nature of ML system analysis. However, the framework’s capability to handle different ML tasks other than multi-class classification still requires further investigation.