In this paper semantic classes of Czech verbs are presented as they are obtained from the lexical database VerbaLex that has recently been built at the NLP Centre FI MU. At the moment we have in VerbaLex 82 semantic classes covering 10,482 Czech verb lemmata and 19,556 verb valency frames. We discuss the criteria for establishing semantic classes: the most important one is grouping verbs according to their senses. The second one exploits relations between semantic classes of Czech verbs and semantic roles and subcategorization features as they are used in VerbaLex valency frames. We also touch on the issue of the ontology that could be used to describe the meanings of the verbs in the semantic classes. The semantic classification of Czech verbs can be extended for other languages via Interlingual Index (ILI) existing in WordNets and it can be used in the various applications in the NLP area (machine translation, syntactic analysis, semantic search, information extraction and others).