Model validation is a critical step in ensuring the accuracy and reliability of model results and is challenging for emerging multi-scale geospatial models. This chapter focuses on the validation of the SIMPLE-G model, which involves economic decisions about land use and water withdrawals at the grid-cell level that are connected to global agricultural markets. The model must simulate complex processes to represent the complexities in observed changes in land-use patterns, which are the result of many mutually interconnected local, regional, and global drivers. Unfortunately, only a few of these models are validated, and validation techniques have been slower to advance than new model developments. In this chapter, we validate the SIMPLE-G model using various methods. We use benchmark replication, backcasting, sensitivity analysis, and uncertainty quantification. These methods help ensure that the model can replicate a base reference condition accurately, model structural processes correctly, identify important parameters, and determine sources of uncertainty in the results.