The invention discloses a method for predicting derailment coefficients in the technical field of railway safety. The method comprises the following steps of: firstly, acquiring left-rail height irregularity data, left-rail rail direction irregularity data, right-rail height irregularity data and right-rail rail direction irregularity data of rails by using a rail inspection vehicle; secondly, by using professional automatic dynamic analysis of mechanical system (ADAMS) / Rail software, simulating the acquired data to obtain data of wheel-rail forces including a vertical wheel-rail force and a horizontal wheel-rail force so as to obtain the derailment coefficients, and normalizing the derailment coefficients; thirdly, by using a selected training sample, training a non-linear auto-regressive with exogenous input (NARX) neural network prediction model; fourthly, testing the trained NARX neural network prediction model, and outputting derailment coefficient data which are tested; and finally, analyzing the derailment coefficient data in a test sample and the derailment coefficient data which are obtained through a tested neural network, and evaluating the performance of the NARX neural network prediction model. By adoption of the method, the derailment coefficients can be accurately predicted, the accuracy in evaluation of railway running safety is improved, and great practical significance is provided for rail traffic safety control.