Financial Well-being (FW) is defined as an individual’s perception of their ability to meet current and future financial obligations and expectations. This paper aims to extract relevant topics from the existing literature on FW by applying text analysis to the documents extracted from the Scopus using the key search term “financial well-being”. A topic model based on Latent Dirichlet Allocation was then applied. The content of the topics was visualized by a word cloud and labeled. A narrative approach was used to provide an interpretation for each topic. The study contributes to the literature on FW in several ways. First, the study raises awareness of the potential for text analysis to uncover previously unknown, high-quality information from large document collections within the field of FW. Second, this is the first paper to construct a topic modeling of the FW literature. Finally, the findings suggest the following main directions for future FW research: (i) extending the analysis to the countries, where FW is understudied; (ii) further analysis of the link between FW and other domains of well-being, between FW and its antecedents, between FW and ‘treatments’ targeted at children and young people, between FW and sustainability; and (iii) a tailored approach to analyzing the resilience of vulnerable groups.