Designing a clinical trial to evaluate the efficacy of an intervention is often complicated by uncertainty over aspects of the study population, potential treatment effects, most relevant outcomes, dropouts, and other factors. However, once participants begin to be enrolled and partial trial data become available, this level of uncertainty is reduced. Adaptive clinical trials are designed to take advantage of the accumulating data during the conduct of a trial to make changes according to prespecified decision rules to increase the likelihood of success or statistical efficiency. Common adaptive rules address early stopping for benefit or futility, sample size reestimation, adding or dropping treatment arms or altering randomization ratios, and changing the eligibility criteria to focus on responder patient subgroups. Adaptive clinical trials are gaining popularity for clinical stroke research. We provide an overview of the methods, practical considerations, challenges and limitations, and potential future role of adaptive clinical trials in advancing knowledge and practice in stroke.