Provided are end-to-end method and system for grading foreign language fluency, in which a multi-step intermediate process of grading foreign language fluency in the related art is omitted. The method provides an end-to-end foreign language fluency grading method of grading a foreign language fluency of a non-native speaker from a non-native raw speech signal, and includes inputting the raw speech to a convolution neural network (CNN), training a filter coefficient of the CNN based on a fluency grading score calculated by a human rater for the raw signal so as to generate a foreign language fluency grading model, and grading foreign language fluency for a non-native speech signal newly input to the trained CNN by using the foreign language fluency grading model to output a grading result.