Saturation in qualitative research is a concept that has gained widespread acceptance as a methodological principle. It is commonly understood as a point at which further data collection and analysis are unnecessary, based on the data collected so far. However, there is uncertainty about how saturation should be conceptualized and used, leading to inconsistencies in its application. This paper explores the different ways saturation is defined and used in qualitative research, identifying four distinct models: theoretical saturation, inductive thematic saturation, a priori thematic saturation, and data saturation. Each model has different assumptions about what saturation is and what is being saturated. The paper also discusses the implications of these models for the purposes and uses of saturation in different qualitative approaches. It argues that saturation should be operationalized in a way that is consistent with the research question and theoretical position, but also that there should be some limit to its scope to maintain its coherence and utility. The paper highlights the uncertain logic underlying saturation, which is essentially a predictive statement about the unobserved based on the observed. This uncertainty can lead to equivocation and confusion in its use. The paper concludes that saturation should be used flexibly, but with clear purposes and considerations of the specific research context. It also emphasizes the need for more transparent reporting of how saturation is achieved in qualitative research.Saturation in qualitative research is a concept that has gained widespread acceptance as a methodological principle. It is commonly understood as a point at which further data collection and analysis are unnecessary, based on the data collected so far. However, there is uncertainty about how saturation should be conceptualized and used, leading to inconsistencies in its application. This paper explores the different ways saturation is defined and used in qualitative research, identifying four distinct models: theoretical saturation, inductive thematic saturation, a priori thematic saturation, and data saturation. Each model has different assumptions about what saturation is and what is being saturated. The paper also discusses the implications of these models for the purposes and uses of saturation in different qualitative approaches. It argues that saturation should be operationalized in a way that is consistent with the research question and theoretical position, but also that there should be some limit to its scope to maintain its coherence and utility. The paper highlights the uncertain logic underlying saturation, which is essentially a predictive statement about the unobserved based on the observed. This uncertainty can lead to equivocation and confusion in its use. The paper concludes that saturation should be used flexibly, but with clear purposes and considerations of the specific research context. It also emphasizes the need for more transparent reporting of how saturation is achieved in qualitative research.