Artemisinin-based combination therapy (ACT) remains a broadly effective anti-malarial drug combination, but the emergence of resistance is threatening its effectiveness. Limiting the spread of these drug-resistant parasites and delaying the emergence of resistance in new areas are of high priority. Understanding the evolution of resistance relies on discerning the fitness costs and benefits associated with resistance mutations. If the cost associated with resistance in an untreated host is sufficiently large relative to the benefit of resistance in a treated host, then the spread of resistance can be mitigated by ensuring sufficient hosts free from that active pharmaceutical ingredient. There is no straightforward way to measure these fitness costs, and each approach that has been used has its limitations. Here, the evidence of fitness costs as measured using field data, animal models, and in vitro models is reviewed for three of the main current or past first-line treatments for malaria: chloroquine (CQ), sulfadoxine-pyrimethamine (SP), and artemisinin derivatives (ART). Despite the difficulties of assessing fitness costs, there is a good amount of evidence of fitness costs in drug-resistant Plasmodium falciparum parasites. The most persuasive evidence comes from resistance reversal observed following the cessation of the use of chloroquine. Comparable evidence cannot be obtained for SP- and ART-resistant parasites, due to the absence of complete cessation of these drugs in the field. Data from in vitro and animal models are variable. While fitness costs are often observed, their presence is not universal across all resistant strains. The extent and nature of these fitness costs can vary greatly depending on the specific genetic factors involved and the ecological context in which the parasites evolve. As a result, it is essential to avoid making broad generalizations about the prevalence or impact of fitness costs in drug-resistant malaria parasites. Focusing on fitness costs as a vulnerability in resistant parasites can guide their evolutionary trajectory towards minimizing their fitness. By accurately predicting these costs, efforts to extend the effectiveness of anti-malarials can be enhanced, limiting resistance evolution and advancing malaria control and elimination goals.