This profiling study deals with the self-regulated learning skills of online learners based on their interaction behaviors on the learning management system. The learners were profiled through their interaction behaviors via cluster analysis. Following a correlational model with the interaction data of learners, the post-test questionnaire data were used to determine self-regulated learning skills scores during the learning process. Regarding the scores, the clusters were named through the prominent interactions of the learners yielding three clusters; actively engaged (Cluster1), assessment-oriented (Cluster2), and passively-oriented (Cluster3), respectively. The profiles in the clusters indicate that assessments were mostly used by the learners in Cluster2, while the frequency of the content tools was high in Cluster1. Surprisingly, some tools such as glossary, survey, and chat did not play a prominent role in discriminating the clusters. Suggestions for future implementations of self-regulated learning and effective online learning in learning management systems are also included.