Crop simulation models are robust tools for scientists, farmers and policymakers that can be used to develop practices and strategies to increase agricultural productivity and sustainability on a local, regional or global scale under conditions and treatments difficult or impossible to test using solely field experimentation. Crop models are increasingly being used to explore solutions to issues such as global food security, climate change impact assessment and adaptation, nitrogen fertilization, irrigation and seasonal variability management. This chapter examines the experimental data sets, dynamic modelling processes and fundamental applications of current wheat (Triticum spp.) crop models, as well as future trends and challenges of wheat crop modelling.