Currently, self-report measures are the primary assessment tool for anxiety disorders. Since they have some limitations, alternative measurements, such as language-based measures, are worth investigating. This paper explores which language markers signal anxiety in fictitious stories written in response to four Thematic Apperception Test (TAT) cards. Participants (n = 492) from a non-probabilistic convenience sample were asked to write a short story next to each TAT card after completing the Generalized Anxiety Disorder-7. We used RoLIWC2015 to conduct the text analysis and applied the LASSO method to identify which language markers predict anxiety. The results showed that the respondents scoring high on anxiety also tend to use more words expressing negative emotions, and fewer words expressing positive emotions. Moreover, their language contained a higher frequency of words that implied semantic differentiation (i.e., but, else) and a lower frequency of words indicating leisure. In conclusion, this paper aims to shed new light on the multimethod assessment of anxiety, mainly focused on specific language signatures as reliable predictors of anxiety symptoms. Further research using more extensive text data is recommended to discover more linguistic markers and improve prediction accuracy.