Video self-modeling (VSM) is an evidence-based intervention for teaching new behaviors that is effective, engaging, and incorporates digital technology. While its utility has been well explored to develop new communication and/or social skills for students with disabilities, fewer studies have examined its use for reading fluency with diverse learners, including those with severe reading deficits, older students, and dual language learners (DLL). The implications of poorly developed reading fluency are serious, and unfortunately, impact many students in today's schools. Educators must find ways to actively engage students in fluency interventions that are evidence-based, build on their strengths, yet are also feasible to implement. The current study employs a multiple baseline design to evaluate the impact of VSM on oral reading fluency, reading errors, and reading self-concept with three seventh-grade DLL students with special needs. Results showed increases in the average number of correct words per minute on familiar passages, and a consistent reduction in errors across participants on familiar and unfamiliar passages. The average effect size (percent of non-overlapping data) across all participants was 0.78, suggesting that VSM may be an effective intervention for older learners, as well as for DLLs with disabilities.