Abstract: Disclosed is a method for predicting medicinal effects wherein medicinal effects of novel compounds are predicted by generating three types of feature data from acquired medicinal substance data, training a neural network model, and then applying acquired new compound data to the neural network model, and the use of the present disclosure mitigates the bottleneck effect of deep learning models and thus the present disclosure can be used to perform a large-scale natural compound study and can perform a preliminary screening of compounds for a large number of candidate medicinal substances, with a high accuracy of medicinal effect prediction.