This entry examines the relationship between data-driven learning (DDL) and second language writing, exploring how corpus-based approaches contribute to various aspects of L2 writing development. The review synthesizes research findings on DDL’s impact on writing as both product and process. As a product, DDL has demonstrated significant effects on lexical diversity, accuracy, lexico-grammar and discourse structure in the text. Studies show DDL’s effectiveness in vocabulary learning, collocation usage and genre-based writing approaches. As a process, DDL supports multiple stages of writing, from planning to revision, with notable success in error self-correction when combined with appropriate teacher mediation. The entry examines different DDL approaches, distinguishing between direct and indirect applications, and their varying effectiveness for different error types and learner proficiency levels. While DDL shows promise in L2 writing instruction, the review identifies the need for greater integration with writing process theories and mainstream curricula. Future directions suggest exploring DDL’s potential in the broader context of writing as cognitive activities, metacognition and self-regulated learning, emphasizing the importance of collaboration between DDL and L2 writing researchers.