While traditional randomized controlled trials (RCTs) randomize individual patients to intervention arms, cluster-randomized trials randomize whole cluster units, which typically represent larger groups of participants such as communities, hospitals, clinics, or surgical practices. This approach is ideal for determining the effects of interventions at the level of the cluster and is best suited for pragmatic trials with systems-level interventions. The cluster trial design is not without its trade-offs, as cluster randomization removes the assumption that outcomes for individual patients are assumed to be independent of one another, one of the key tenets of parallel arm RCTs. This results in relatively less statistical power in cluster-randomized trials, requiring larger sample sizes and complex statistical analyses than parallel arm RCTs. Despite these challenges, cluster-randomized trials play a role in evaluating certain types of interventions, and if done correctly are an essential tool for the surgical clinical trialist.