The　slump　of　fresh　concrete　depends　on　three　parameters-nominal　water-cement　ratio　of　concrete,　average　paste　thickness　of　aggregates　and　fly　ash-binder　ratio.　Applying　two　concepts　of　characteristic　diameter　and　eigenpacking　degree,　the　differences　between　theoretical　model　and　actuality　of　fine　and　coarse　aggregates　can　be　eliminated.　Based　on　the　calculation　methods　of　nominal　water-cement　ratio　of　concrete　and　average　paste　thickness　of　aggregates　provided　by　authors,　the　nonlinear　relation　ship　between　slump　of　fresh　concrete　and　nominal　water-cement　ratio　of　concrete,　average　paste　thickness　of　aggregates,　fly　ash-binder　ratio　is　established　by　applying　artificial　neural　network.　The　outcome　of　the　study　can　be　used　to　reduce　the　number　of　trial　and　error　in　concrete　mix　proportion　design,　save　cost　and　labor,　and　can　lay　the　foundation　of　mix　proportion　design　of　higher　volume-stability　concrete.