In recent years, herbicide resistance has attracted much attention as an increasingly urgent problem worldwide. Unfortunately, most of that effort was focused on confirmation of resistance and characterization of the mechanisms of resistance. For management purposes, knowledge about biology and ecology of the resistant weed phenotypes is critical. This includes fitness of the resistant biotypes compared with the corresponding wild biotypes. Accordingly, fitness has been the subject of many studies; however, lack of consensus on the concept of fitness resulted in poor experimental designs and misinterpretation of the ensuing data. In recent years, methodological protocols for conducting proper fitness studies have been proposed; however, we think these methods should be reconsidered from a herbicide-resistance management viewpoint. In addition, a discussion of the inherent challenges associated with fitness cost studies is pertinent. We believe that the methodological requirements for fitness studies of herbicide-resistant weed biotypes might differ from those applied in other scientific disciplines such as evolutionary ecology and genetics. Moreover, another important question is to what extent controlling genetic background is necessary when the aim of a fitness study is developing management practices for resistant biotypes. Among the methods available to control genetic background, we suggest two approaches (single population and pedigreed lines) as the most appropriate methods to detect differences between resistant (R) and susceptible (S) populations and to derive herbicide-resistant weed management programs. Based on these two methods, we suggest two new approaches that we named the “recurrent single population” and “recurrent pedigreed lines” methods. Importantly, whenever the aim of a fitness study is to develop optimal resistance management, we suggest selecting R and S plants within a single population and evaluating all fitness components from seed to seed instead of measuring changes in the frequency of R and S alleles through multigenerational fitness studies.