In this paper, we propose a supervised approach for toxic comment classification for French language. We choose a set of features proposed for toxic comment detection for English and use it for French toxic comment detection. Our approach is based on N-gram features, linguistic features and a dictionary of insulting words and expressions. We obtain a F1-score of 78% with N-grams, linguistic and lexicon features, a precision of 87% with N-gram features and a recall of 83% with N-gram, linguistic and lexicon features. Classifiers used are linear SVM and decision tree.