Quantitative　structure-activity　relationship　(QSAR)　model　was　developed　for　predicting　the　mutagenicity　of　aromatic　compounds.　The　log　revertants　data　of　S.　typhimurium　TA98　strain　from　Ames　test　have　been　collected.　225　aromatic　compounds　were　randomly　divided　into　the　training　set　with　186　molecules　and　test　set　with　39　molecules.　Multiple　linear　regression　(MLR)　analysis　was　used　to　select　six　descriptors　from　thousands　of　descriptors　calculated　by　semi-　empirical　AM1　and　E-dragon　methods.　The　final　QSAR　model　with　six　descriptors　was　internal　and　external　validated.　In　addition,　to　validate　the　utility　of　our　QSAR　model　for　the　chemical　evaluation,　three　aromatic　compounds　were　taken　to　test　the　predictive　ability　and　reliability　of　the　model　experimentally.　The　compounds　selected　for　testing　were　not　based　on　the　predictions,　thus　spanning　the　range　of　predicted　probabilities.　The　subsequently　generated　results　of　the　Ames　test　were　in　good　correspondence　with　the　predictions　and　confirmed　this　approach　as　a　useful　means　of　predicting　likely　mutagenic　risk　of　aromatic　compounds.