The present study is part of a project aiming at empirically investigating the process of modeling the partner’s knowledge (Mutual Knowledge Modeling or MKM) in Computer-Supported Collaborative Learning (CSCL) settings. In this study, a macro-collaborative script was used to produce knowledge interdependence (KI) among colearners by providing them with different but complementary information. Prior to collaboration, two students read the same text in the “Same Information” (SI) condition while each of them read one of two complementary texts in the “Complementary Information” (CI) condition. After the collaboration phase, a knowledge modeling questionnaire asked participants to estimate both their own — and their partner’s outcome knowledge thanks to Likert-type scales. The relation between the accuracy with which co-learners assess their partner’s knowledge and learning has been examined. In addition, we investigated the KI effect on (a) learning performance and (b) the MKM accuracy. Finally, we wondered to what extent the MKM accuracy could mediate the KI effect on learning. Results showed no difference in learning performance between participants who worked on same information and participants who worked on complementary information. We also found that participants were more accurate at assessing their partner’s knowledge in the SI condition than in the CI condition. The discussion focuses on methodological limitations and provides new directions for investigating the KI effect on MKM accuracy.