Assessing the potential carcinogenicity of chemicals for humans represents an ongoing challenge. Chronic rodent bioassays predict human cancer risk at only limited reliability and are simultaneously expensive and long lasting. In order to seek for alternatives, the ability of a transcriptomics-based primary mouse hepatocyte model to classify carcinogens by their modes of action was evaluated. As it is obvious that exposure will induce a cascade of gene expression modifications, in particular, the influence of exposure time in vitro on discriminating genotoxic (GTX) carcinogens from nongenotoxic (NGTX) carcinogens class discrimination was investigated. Primary mouse hepatocytes from male C57Bl6 mice were treated for 12, 24, 36, and 48 h with two GTX and two NGTX carcinogens. For validation, two additional GTX compounds were studied at 24 and 48 h. Immunostaining of gammaH2AX foci was applied in order to phenotypically verify DNA damage. It confirmed significant induction of DNA damage after treatment with GTX compounds but not with NGTX compounds. Whole-genome gene expression modifications were analyzed by means of Affymetrix microarrays. When using differentially expressed genes from data sets normalized by Robust Multi-array Average, the two classes and various compounds were better separated from each other by hierarchical clustering when increasing the treatment period. Discrimination of GTX and NGTX carcinogens by Prediction Analysis of Microarray improved with time and resulted in correct classification of the validation compounds. The present study shows that gene expression profiling in primary mouse hepatocytes is promising for discriminating GTX from NGTX compounds and that this discrimination improves with increasing treatment period.