Estimating　evaporation　is　one　of　the　most　important　works　for　meteorologists　and　hydrologists.　This　paper　employed　three　artificial　neural　network　(ANN)　algorithms,　which　are　linear　regression　(LR),　multi-layer　perceptron　(MLP)　and　general　regression　neural　network　(GRNN),　to　investigate　the　possibility　to　apply　ANNs　in　forecasting　evaporation　level.　The　data　used　in　this　study　are　observed　values　of　meteorological　variables　from　a　weather　observatory　in　Beijing.　Temperature,　air　pressure　and　wind　speed　are　three　factors　affect　the　level　of　evaporation　most.　The　study　also　employed　k-fold　cross-validation　technique　to　avoid　overfitting　and　improve　the　performance　of　the　models.　Mean　absolute　error　(MAE),　root　mean　square　error　(MASE)　and　coefficient　of　determination　(R2)　statistics　are　used　to　evaluate　the　performance　of　the　models　and　the　performance　of　MLP　is　roughly　same　as　GRNN,　which　is　higher　than　LR.　The　result　shows　that　ANN　is　a　kind　of　accurate　and　reliable　methods　to　predict　evaporation.　©　2020　ACM.