Reaction features consist of prior feasibility score and molecular embedding for each reaction and fingerprint of target compound. To calculate reaction prior feasibility, a statistical analysis of the in-house reaction data subset was performed. Reactions were labeled as "successful" if their yield was recorded to be more than 20 percent and labeled "unsuccessful" if their yield was recorded as zero along with a conclusion phrase "Reaction failed". All labeled reactions were then grouped by reaction class as identified by the NameRxn software. Each reaction class was given points for the total number of successful experiments and the average success rate of reactions belonging to a certain reaction class. The specific point allocation system and evaluation criteria are shown in Table . As a result of this method, each individual reaction gets a number between 0 and 6, depending on the reaction class it belongs to. In order to perform predictions on the reactions, we represent these reactions through embedding functions which take the SMILES string representation of a reaction as an input and outputs its numerical embedding. In our experiments, we tested three different methods of embedding described below, comparing them with a baseline model where we only use the reaction class feasibility as an input for the route feasibility.