Aimed at providing efficient training data for neural translation quality estimation model, a pseudo data construction method for target dataset is proposed, the model is trained by two stage model training method: pre training based on pseudo data and fine tuning. The experimental design of different pseudo data scale is carried out. The experiment results show that the machine translation quality estimation model trained by the pseudo data has significantly improved in the correlation between the scores given by human and the artificial scores.