Sustainability is a holistic and complex multi-dimensional concept encompassing economic, social and environmental issues, and its assessment is a key step in the implementation of sustainable agricultural systems. Realistic assessments of sustainability require: (1) the integration of diverse information concerning economic, social and environmental objectives; and (2) the handling of conflicting aspects of these objectives as a function of the views and opinions of the individuals involved in the assessment process. The assessment of sustainability is therefore increasingly regarded as a typical decision-making problem that could be handled by multi-criteria decision-aid (MCDA) methods. However, the number and variability of MCDA methods are continually increasing, and these methods are not all equally relevant for sustainability assessment. The demands for such approaches are also rapidly changing, and faster ex ante assessment approaches are required, to address scales currently insufficiently dealt with, such as cropping system level. Researchers regularly carry out comparative analyses of MCDA methods and propose guidelines for the selection of a priori relevant methods for the assessment problem considered. However, many of the selection criteria used are based on technical/operational assumptions that have little to do with the specificities of ex ante sustainability assessment of alternative cropping systems. We attempt here to provide a reasoned comparative review of the main groups of MCDA methods, based on considerations related to those specificities. The following main guidelines emerge from our discussion of these methods: (1) decision rule-based and outranking qualitative MCDA methods should be preferred; (2) different MCDA tools should be used simultaneously, making it possible to evaluate and compare the results obtained; and (3) a relevantly structured group of decision-makers should be established for the selection of tool variants of the choosen MCDA methods, the design/choice of sustainability criteria, and the analysis and interpretation of the evaluation results.