Recent regulations on biofuels require reporting of greenhouse gas (GHG) emission reductions related to feedstock-speciﬁc biofuels. However, the inclusion of GHG emissions from land-use change (LUC) into law and policy remains a subject of active discussion, with LUC–GHG emissions an issue of intense research. This article identiﬁes key modelling choices for assessing the impact of biofuel production on LUC–GHG emissions. The identiﬁcation of these modelling choices derives from evaluation and critical comparison of models from commonly accepted biofuels–LUC–GHG modelling approaches. The selection and comparison of models were intended to cover factors related to production of agricultural-based biofuel, provision of land for feedstock, and GHG emissions from land-use conversion. However, some fundamental modelling issues are common to all stages of assessment and require resolution, including choice of scale and spatial coverage, approach to accounting for time, and level of aggregation. It is argued here that signiﬁcant improvements have been made to address LUC–GHG emissions from biofuels. Several models have been created, adapted, coupled, and integrated, but room for improvement remains in representing LUC–GHG emissions from speciﬁc biofuel production pathways, as follows: more detailed and integrated modelling of biofuel supply chains; more complete modelling of policy frameworks, accounting for forest dynamics and other drivers of LUC; more heterogeneous modelling of spatial patterns of LUC and associated GHG emissions; and clearer procedures for accounting for the time-dependency of variables. It is concluded that coupling the results of different models is a convenient strategy for addressing effects with different time and space scales. In contrast, model integration requires uniﬁed scales and time approaches to provide generalised representations of the system. Guidelines for estimating and reporting LUC–GHG emissions are required to help modellers to deﬁne the most suitable approaches and policy makers to better understand the complex impacts of agricultural-based biofuel production.