This paper presents a method to integrate the model adaptation technique and the missing feature theory for robust speech recognition. The recognition performance can be further improved as comparing with that utilizing only a single approach. The basic idea comes from that the integration of two techniques will compensate two improper assumptions made separately by these two techniques. The evaluation of the proposed method on the task of isolated Mandarin digits recognition shows that the system robustness is upgraded substantially.