Abstract Through usage of a large number of cosmetic products, consumers are very often exposed to toxic chemicals. This paper is aimed at proposing a model for the prediction of chemical functions and weight fractions in these products based on the structural and physical-chemical properties of the chemicals. Due to the imbalance of classes we used Support Vector Machine (SVM) method, which can complement a smaller class with the examples that are most similar to it and identify the examples that are most different. The generality of the SVM method was additionally enhanced by combining it with ensemble Bootstrap Aggregation (Bagging). The research results show that the proposed bagging SVM method can overcome the disadvantages of previously applied methods. Further, it can help address the lack of information needed to assess exposure to risk from the use of cosmetic products containing toxic chemicals in their composition. The proposed models can be applied to predict whether a certain chemical may be a substitute for a function performed by another possibly toxic chemical in a cosmetic product, as well as well as to determine the quantity proportion of a certain dangerous chemical on the basis of its chemical structure and physical-chemical properties.