Models, created using different modeling formalisms or techniques, usually serve different purposes and provide unique insights. While each modeling technique might be capable of answering specific questions, complex problems require multiple models interoperating to complement/supplement each other. This Multi-Modeling approach for solving complex problems is full of syntactic and semantic challenges. In this chapter, a systematic methodology for addressing Multi-Modeling problems is presented. The approach is domain specific: domain identification and domain analysis are the first steps in which the multi-modeling concepts and modeling techniques associated with a domain of interest are identified and analyzed. Then a new Domain Specific Multi-Modeling Workflow Language supported with a domain ontology is used to construct the workflow that defines the interoperation of the selected models. The domain ontology provides semantic guidance to affect valid model interoperation. This general approach is illustrated using a case study from the Drug Interdiction and Intelligence application domain. Analysis of diverse intelligence and sensor data using various modeling techniques is essential in identifying the best courses of action. For this example, the created workflow focuses on the interoperation of Social Networks, Timed Influence Nets, and Geospatial Models.