Abstract: Embodiments are directed to generating an interactive visual framework to review decision making of machine learning model analysis based on employing a machine learning algorithm to identify patterns in scenario data, map those patterns to dimension values, and generate a machine learning model that represents decision sequences leading to specific outcomes. A generated inference method may predict scenario outcomes based on these correlations and a predetermined threshold, providing valuable insight into potential results. An interactive visual framework may be generated based on the dimension values. The interactive visual framework may be dynamically updated to reflect changes in the machine learning model metadata. This interactive visual framework links normalized dimension values, offering intuitive understanding of the underlying decision-making process. Furthermore, the system is capable of generating sequences of inference methods that enhance predictive capabilities and adaptability.