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Road safety is one of the most important things in carrying out transportation. One effort to improve road safety is to reduce the number of traffic accidents. By knowing the accident data at a location, transportation planners can conduct analysis so that they can provide recommendations for improvements, handling and strategies for improving road safety. However, the prediction model in Indonesia in some studies is more local purposes. Meanwhile the prediction model used in various countries needs to be adapted to the conditions of Indonesia. This study aims to develop Safety Performance Functions (SPFs) for estimating the number of traffic accidents that can be used to predict the number of accidents on national rural road segments by looking at the characteristic of road condition in Indonesia with the Generalized Linear Model (GLM) approach and Empirical Bayes (EB). The availability of data in the form of a web-based accident database from the National Police Corps and the time series data from 8 provinces in Indonesia allows this research to be carried out. The model developed is expected to function as an evaluation tool and decision maker in its contribution to improving road safety in Indonesia.