We study methods of collective decision-making—an important capability for a swarm to become autonomous. This chapter introduces collective decision-making as a key capability for enabling autonomous swarms to act intelligently at the macroscopic level. It reviews foundational ideas from individual and group decision-making, including challenges such as consensus formation and the Byzantine Generals Problem, and surveys a broad set of modeling approaches (e.g., urn models, voter and majority rule dynamics, Hegselmann–Krause, Kuramoto, and Ising models) to guide model selection. Practical implementations are illustrated through experiments with Kilobots and e-pucks, highlighting the processes of consensus formation and the tradeoff between speed and accuracy. The chapter also addresses swarm-specific challenges, including local communication limits, decision-making under uncertainty, optimal stopping strategies (e.g., the 1/e rule, Chao1), and the influence of contrarian agents. Together, these perspectives provide both theoretical and practical foundations for designing and analyzing self-organizing swarm systems.