It is an expensive and time-consuming task to develop a new model. Furthermore, a single model often cannot provide answers required for complex decision making based on multiple criteria. Coupling models are often applied to make use of existing models and analyze complex policy questions. This paper provides an overview of possible model integration approaches, briefly explains the modules that were integrated in a particular application, and focuses on the integration methods applied in this research. While the initial attempt was to integrate all models as tightly as possible, the authors developed a much more agile integration approach that allows adding and replacing individual modules easily. Python wrappers were developed to loosely couple land use, land cover, transportation, and emission models developed in different environments. ArcGIS Model Builder was used to provide a graphical user interface and to present the models’ workflow. The suggested approach is especially efficient when the models are developed in different programming languages, their source codes are not available, or the licensing restrictions make other coupling approaches impractical.