Traditional personal authentication methods have many instinctive defects. Biometrics is an effective technology to overcome these defects. The unimodal biometric systems, which use a single trait for authentication, can result in some problems like noisy sensor data, non-universality and/or lack of distinctiveness of the biometric trait, unacceptable error rates, and spoof attacks. These problems can be addressed by using multi-biometric features in the system. This paper investigates the fusion of palmprint and iris for personal authentication. The features of the palmprint and the iris are first extracted and matched respectively. Then these matching distances are normalized. Finally, the normalized distances are fused to authenticate the identity. The experimental results show that combining palmprint and iris can dramatically improve the accuracy of the system.