Given the strong influence of vocabulary knowledge on L2 learners’ text comprehension (Schmitt et al., 2011), assessing the vocabulary demands of foreign language (L2) input is a crucial challenge for both L2 educators and researchers. To do so, a well-established step for the design, selection, and empirical analysis of L2 input is to use tools for lexical profiling. This involves categorising a text’s vocabulary across levels in a word frequency list to estimate the vocabulary knowledge learners need in order to achieve satisfactory comprehension. However, current tools are mainly available for English and are built on word family-based frequency lists derived from broad corpora, which have been suggested to have more limited predictive power of learner knowledge than previously presumed (Schmitt et al., 2021). This article presents LexPro, a new plurilingual lexical profiling tool which was programmed in Python and facilitates analysis of individual texts and corpora in English, French, Spanish, and Dutch. It relies on flemmatised word frequency lists derived from subtitle corpora, on the empirical ground that these are more reflective of learner knowledge (Pinchbeck et al., 2022). Output includes general text characteristics (e.g., text length, lexical diversity), a lexical profile with accompanying visuals, an overview of the used vocabulary, and detailed insights into word repetition as well as the number of texts in which words appear. To illustrate the potential applications of the tool for both research and teaching practice, a use case is presented analysing an Intermediate French L2 textbook. The paper concludes with practical recommendations for implementing LexPro in educators’ text selection processes.
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