Generalizability Theory (G-Theory) is a statistical method used to analyze data collected by means of quantitative measures. In cases where there is a limited amount of data collected from a specific testing situation, it provides techniques to estimate the generalizability of those influences that are due to any specific factor (e.g., occasion) to all possible situations and contexts. Mindfulness can be conceptualized as either a state or a trait, but traditional psychometric indicators such as test-retest reliability fail to distinguish clearly between the two in psychological measures. Notwithstanding the clinical effectiveness of mindfulness, any specific element of mindfulness treatment can only be evaluated by comparing state and trait changes using techniques that allow such changes to be measured. G-Theory is a suitable method to differentiate between state and trait variance components, and its application has been demonstrated with empirical examples of mindfulness, self-compassion, stress, depression, schizophrenia, traumatic brain injury, subjective and cognitive complaints. Generalizability analysis is also unique and beneficial to examine specific sources of true and error variance in any measurement design. This chapter describes special features of G-Theory and its applicability to examine various error sources and to distinguish between state and trait components in a measure. It emphasizes the value of G-Theory to enhance both reliability and validity in mindfulness assessment.