Data-driven learning (DDL) is considered a promising approach for effectively enhancing the writing performance of second language (L2) learners. Although extensive research has explored the use of DDL in developing various aspects of writing skills, few studies have focused on its potential for revising writing. Moreover, few existing studies have examined DDL at the revision stage using complexity, accuracy, and fluency (CAF) measures as objective and reliable indices of writing quality. This entry explores the intersection of DDL and the CAF framework in L2 writing development. Following a brief discussion of DDL and CAF measures within L2 writing, this entry presents the empirical studies applying these measures within DDL contexts, discussing the methodologies and findings in detail.