Secondary data analysis has emerged as an important approach for researchers seeking to explore new research questions using existing datasets. These datasets often comprise large and diverse, as well as longitudinal data, enabling comprehensive analyses that might be impractical through primary data collection alone. This paper discusses the importance of secondary data analysis in breastfeeding research, provides examples of publicly available and restricted datasets containing breastfeeding variables, outlines the methodological steps in conducting secondary data analysis, and discusses common limitations associated with this approach. By emphasizing both the utility and challenges of secondary data analysis, the paper aims to encourage informed use of secondary data analysis to advance knowledge and address important research questions in breastfeeding.