Judgment aggregation studies the aggregation of yes-no judgments of the members of a jury on logically interconnected propositions into a consistent collective judgment set. As the discursive dilemma shows, proposition-wise majority voting will not in general lead to a consistent collective judgment set. To arrive at a consistent collective judgment set, three procedures have been discussed in the literature: the premise-based procedure (PBP), the conclusion-based procedure (CBP) and the distance-based procedure (DBP). According to these procedures, the jury can accept a judgment set that only a few (or even none) of the members of the jury voted for. This raises the question whether such a decision is really acceptable. Clearly, a decision based on PBP, CBP or DBP amounts to a compromise, and not everybody will be happy with the decision. The jury members agree to go along with the will of the others. The preferred solution, however, is to arrive at a consensus, whereby every jury member is in agreement with the final decision. The goal of this paper is to develop a model for the emergence of consensus in a judgment aggregation setting and to ask how this new aggregation method compares with suitably generalized versions of PBP, CBP and DBP. This work has implications for the philosophy of science, which I will explore at the end of the talk. The talk is based on joint work with Gabriella Pigozzi (Luxembourg) and Jan Sprenger (Tilburg). Background reading: 1. S. Hartmann and J. Sprenger: Judgment Aggregation and the Problem of Tracking the Truth. http://philsci-archive.pitt.edu/archive/00004042/ 2. S. Hartmann, G. Pigozzi and J. Sprenger: Reliable Methods of Judgment Aggregation. http://philsci-archive.pitt.edu/archive/00003593/