A multiagent system should be capable of fast and flexible decision-making to successfully manage the uncertainty, variability, and dynamic change encountered when operating in the real world. Decision-making is fast if it breaks indecision as quickly as indecision becomes costly. This requires fast divergence away from indecision in addition to fast convergence to a decision. Decision-making is flexible if it adapts to signals important to successful operation, even if they are weak or rare. This requires tunable sensitivity to input for modulating regimes in which the system is ultrasensitive and in which it is robust. Nonlinearity and feedback in the decision-making process are necessary to meeting these requirements. This article reviews theoretical principles, analytical results, related literature, and applications of decentralized nonlinear opinion dynamics that enable fast and flexible decision-making among multiple options for multiagent systems interconnected by communication and belief system networks. The theory and tools provide a principled and systematic means for designing and analyzing decision-making in systems ranging from robot teams to social networks. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 7 is May 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.