Research has consistently demonstrated that learners are strikingly poor at metacognitively monitoring their learning and comprehension of texts. The aim of the present meta-analysis is to explore three important questions about metacomprehension: (a) To what extent can people accurately discriminate well-learned texts from less well learned ones? (b) What are the (meta)cognitive causes of poor metacomprehension accuracy? and (c) What interventions improve the accuracy of metacomprehension judgments? In total, the meta-analysis integrated 502 effects and data from 15,889 participants across 115 studies to assess these questions. The results showed a weighted mean correlation of.178 for nonintervention effects. Many interventions were shown to be effective, such as delayed summary writing and delayed keyword generation. In addition, combining different interventions tended to generate additive benefits. The findings support the transfer-appropriate monitoring account, the situation model framework, and the poor-comprehension theory as explanations for why metacomprehension accuracy is typically poor. Practical implications are discussed.