This article explores the application of snowball sampling, a non-probability sampling technique, in recruiting hard-to-reach and underserved populations for health education programs and research studies. The authors, including Georgia Robins Sadler, Hau-Chen Lee, Rod Seung-Hwan Lim, and Judith Fullerton, provide examples from their own research to demonstrate how adaptations of snowball sampling can effectively engage traditionally marginalized groups. The article highlights the cultural sensitivity and trust-building aspects of snowball sampling, which can enhance participation rates and reduce bias. However, it also discusses the limitations, such as the lack of statistical reliability in estimating sample saturation and the risk of personal information disclosure. The authors emphasize the importance of ethical considerations, particularly in protecting the privacy of participants and sources. They conclude that while snowball sampling has its advantages, it should be carefully evaluated against probability sampling methods to ensure the generalizability of research findings.This article explores the application of snowball sampling, a non-probability sampling technique, in recruiting hard-to-reach and underserved populations for health education programs and research studies. The authors, including Georgia Robins Sadler, Hau-Chen Lee, Rod Seung-Hwan Lim, and Judith Fullerton, provide examples from their own research to demonstrate how adaptations of snowball sampling can effectively engage traditionally marginalized groups. The article highlights the cultural sensitivity and trust-building aspects of snowball sampling, which can enhance participation rates and reduce bias. However, it also discusses the limitations, such as the lack of statistical reliability in estimating sample saturation and the risk of personal information disclosure. The authors emphasize the importance of ethical considerations, particularly in protecting the privacy of participants and sources. They conclude that while snowball sampling has its advantages, it should be carefully evaluated against probability sampling methods to ensure the generalizability of research findings.