This presentation reports on the development of software that enables EFL learners to perform simple analyses of texts in order to build personalized word lists, which can be stored in a cloud system for review. It will begin by providing a pedagogical rationale for the system by surveying previous literature. This will be followed by a demonstration of the software, its capabilities, and how it was developed. The programming language used is primarily Python, and makes use of open-source Python libraries, Natural Language Toolkit (NLTK) and Pandas. The text-analysis tool draws on data provided by several commonly used word lists, as well as custom lists developed within the researcher’s university in order to provide learners with information about words that they encounter in texts. After learners have decided on the vocabulary they wish to review, they are able to store these words in a spaced repetition system (SRS) for efficient review. While variations of similar tools exist already, the combination of text analysis tools with an SRS provides learners with a convenient and flexible way to develop personalized vocabulary lists. It is also unique in that it is aimed to suit Japanese EFL learners in tertiary education.