Model-based systems thinking (MBST) is a rigorous method (framework, languages, and tools) that integrates various modeling methods that have proven their value to augment our capability for understanding real-world problems but were not previously directly aligned with adding rigor to the application of systems principles of Chapter 5 . Currently, the most useful modeling methods in MBST are system dynamics, stochastic, agent-based, AI/ML-based, and architectural modeling. MBST augments our limited capabilities to make real-world problems easier to understand. It is a force multiplier for applying the systems principles and ways of the systems thinker into our approach and behavior. MBST augments our approach regardless of whether the problem fits the STEM, non-STEM, sociotechnical, social science, or, in general, some transdisciplinary space that includes several core disciplines. The MBST method is an extended version of the system dynamic method by John Sterman (Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill, 2000). The MBST method was created to enhance the teaching and enforce the application of systems thinking principles (listed in Chapter 5 ) in the SYSE 532 Class taught at Colorado State University.