Multi-model ensembles (MME) are key ingredients for future climate projection and the quantification of its uncertainty. Developing robust protocols to design balanced and complete computer experiments for MME is a matter of active research. In this study, we take advantage of a large-size MME produced for Greenland ice sheet contributions to future sea level by 2100 to define a series of computer experiments that are closely related to practical MME design decisions: what is the added value of including specific set of experiments in the projections, i.e. either adding new models (Regional Climate Model RCM, or Ice Sheet Model ISM) or extending the range of some parameter values. By using these experiments to build a random-forest-based emulator, changes in the emulator’s predictive performance and the emulator-based probabilistic projections provided information on several aspects: (1) the utmost importance of including the SSP5-8.5 scenario, due to the large number of simulations available and the range of global warming they cover; (2) the importance of having diverse ISM and RCM models; (3) the lesser importance of the choice in the range of the Greenland tidewater glacier retreat parameter. We expect these recommendations to be informative for the design of next generations of MME, in particular for the next Ice Sheet Model Intercomparison Project ISMIP7 in preparation.