Cultural values have long been the objects of crimes, among which the export from the state stands out. Falsification hides artworks from customs control and its detection requires a long examination using a variety of methods of analysis. This article discusses the task of verifying painting’s authenticity during customs inspection. A two-stage procedure is proposed, which includes a quick check based on the analysis of painting’s images and a longer museum expertize. To implement the image analysis, it is proposed to use an intelligent decision-making system, which is based on a classifier that implements the k-nearest neighbors algorithm. A set of features to describe painting’s properties is formed, metrics for calculating the similarity measure on objects in the course of classification is proposed. To train an algorithm, a dataset is proposed, which includes paintings by world and European artists, as well as Ukrainian painters from different centuries.