The widespread use of biometrics and its increased popularity introduces privacy risks. In order to mitigate these risks, solutions such as the helper-data system, fuzzy vault, fuzzy extractors, and cancelable biometrics were introduced, also known as the field of template protection. Besides these developments, fusion of multiple sources of biometric information have shown to improve the verification performance of the biometric system. Our work consists of analyzing feature-level fusion in the context of the template protection framework using the helper-data system. We verify the results using the FRGC v2 database and two feature extraction algorithms.