The noise map can be applied to predict the effect of noise and establish the noise reduction measure. But the predicted value in the noise map can vary depending on the input variables. Thus, we surveyed the several prediction models and analyzed the changes corresponding to the variables for obtaining the coherency and accuracy of prediction results. As a result, we know that the Schall03 and CRN model can be applied to predict the railway noise in Korea and the correction value, such as bridges correction, multiple reflection correction, curve correction must be used for reflecting the condition of the prediction site. Also, we know that the prediction guideline is an essential prerequisite in order to obtain the unified and accurate predicted value for railway noise.