As New Zealand farming industry pursues more productivity this has implication for environment and makes land use and agricultural policy decision processes more complex for which integrated assessment modeling (IAM) can support. The purpose of this review paper is to propose means through which IAM can be improved specifically to minimize uncertainties and increase relevance, reliability, and utility of outputs of different models. Literature suggests that the general motivation for land use change is that farmers do consider the environment, but need to maintain profitability. There are handful decision support tools for land use and land policy decisions but one common feature of most of the models is that each seems suitable for only a part of the complexity. An appropriate framework for linking different models in an integrated assessment is still needed. As integrated assessment often goes beyond an individual researcher‘s role, research institutions need to align their research portfolio across the dimensions of the complexity by creating an appropriate mechanism to integrate individual research into integrated assessments while individual researchers need to present modelling results in a compatible format for integration into another model‘s application.