This paper proposes the system identification method for linear system with time delay and unknown order. We hypothesize some candidate models which have different order, because system order is unknown. In each model, we estimate the model's parameters based on maximum likelihood method by using non-linear optimization technique. Then both local optimization technique and global search method are used because the estimated parameters may fall into local minimum. After all candidate model's parameters are estimated, one model is selected among these models to estimate system order by using a posteriori probability based on Bayes' theorem. Finally, the validity of proposed method is shown by numerical example.