The current work describes the interaction with various stakeholder groups to establish consensus on stage-gate specific criteria that human risk assessment (HRA) models for manufactured nanomaterials (MN) need to comply with. During the decisive steps in the innovation process, which can be described in a simplified way as stage-gates, it is decided that an innovation makes it either to launch, or is cancelled during one of these stages. However, at present, it is unknown which current HRA models for MN, can assist in this decision making process and to which extent refinements of these models are needed. To accomplish these goals, several steps were performed: (1) the development of criteria for risk assessment along stage-gates; (2) the active involvement of stakeholders and possible end-users to assign values to these criteria; (3) the inventory, selection and assessment of HRA models according to the developed criteria; (4) the matching of the HRA models to the criteria, assessed by the stakeholders, in order to propose a ranking of existing models and (5) exploration of the model mismatches with stage-gate specific criteria and discussion of current model limitations. The assessment led to a ranking of the models for each of the stage-gates. Two HRA models appeared to be predominantly applicable for all stage-gates, namely the NanoSafer CB and the GUIDEnano tool, where NanoSafer CB scored highest for stage 2 and 3 (scoping and business case) and GUIDEnano tool for stage 4–7 (R&D, testing and validation, launch and monitoring). NanoSafer CB only covers occupational human health. LICARA nanoSCAN scored high for the earlier stages (stage 2, 3 and 4) and scored less for the later stages. RiskofDerm was listed for all stages except stage 3 and 7. ECETOC TRA was represented in stages 3–7, and Stoffenmanager (nano), EGRET2 and ART were applicable for one or two stages. Based on these results, it was possible to prioritize Nanosafer CB, GUIDEnano, RiskofDerm, LICARA nanoSCAN and Stoffenmanager Nano. Of these five models, limitations consisted of e.g. expertise required to use the model, interpretation of the data, quality assessment of the input parameters, consideration of different endpoints and populations (such as children, workers, consumers). Practically, this work provides a prioritization for end users of useful models, among the plethora of different models available, towards HRA of MN. Further, it identifies suggestions for future model improvements, enabling the ultimate practical application in the decision making process during the development of MN or MN containing products. © 2019