We develop a scoring system that assigns scores that reflect the relative quality of synthetic routes based on the target molecule. This model predicts the TED score of any synthetic route without knowing the reference route. The information of all reactions in one route is processed as route encoding, combined with other route features such as complexity and cost, is used to predict the final TED score. We will refer to the reaction-level processing network as the encoder network, and the route score prediction network as the scorer network.