Data-based individualization (DBI) is a systematic process used to guide teachers in making decisions related to students' responsiveness to intervention. Whereas this process has been used extensively with academic interventions, far less is known about DBI used within the context of behavioral interventions. In this study, elementary general and special education teachers (a) implemented a technology-based, self-monitoring intervention with students exhibiting challenging behavior; and (b) used DBI to evaluate student progress and make intervention adaptations accordingly. Results of multilevel modeling indicated students improved their positive behavior significantly (p < 0.001) from baseline to intervention. For most students, once they began intervention, positive behaviors either maintained or increased gradually when teachers made adaptations to the self-monitoring intervention. In addition to these results, an analysis of the effects of different intervention adaptations (e.g., raising or lowering goals, increasing or decreasing interval length) and visual analysis of individual students' response are discussed.