Given the recognized role of agroforestry systems (AFS) in climate change mitigation through carbon sequestration, it is important to have rigorous and consistent procedures to measure the extent of C sequestration. The methods used currently vary widely and the estimations entail several assumptions, some of which are erroneous. Large-scale global models that are based on such measurements and estimations are thus likely to result in serious under- or overestimations. These methodological problems, though common to most land-use systems, are of a higher order of magnitude in AFS compared with agricultural systems because of the integrated nature of AFS and the lack of rigorous data on the area under the practice. While there are no easy, fast, and pragmatic solution to these complex issues in the short term, agroforestry researchers could, at the very minimum, include accurate description of the methods and procedures they use, such as sampling scheme, analytical details, and computational methods, while reporting results. That will help other researchers to examine the datasets and incorporate them in larger databases and help agroforestry earn its deserving place in mainstream efforts. Missing the opportunity to capitalize on the environmental services of agroforestry for the lack of rigorous and consistent procedures for data collection and reporting will be a serious setback to the development of agroforestry.