As　one　of　efficient　and　good-adaptability　welding　methods,　pulsed　gas　metal　arc　welding(P-GMAW)　has　been　applied　in　industrial　production　widely.　In　this　paper,　the　modeling　and　simulation　methods　in　P-GMAW　shape　process　of　low　carbon　steel　were　studied.　Firstly,　a　series　of　BP　neural　network　dynamic　models　were　established　for　P-GMAW　shape　process;　then　stable-state　and　dynamic　simulations　were　implemented　with　these　modes　to　reveal　the　welding　form　rules　in　P-GMAW.　Meanwhile,　this　paper　proposes　a　method　that　using　the　neural　network　model　to　investigate　the　relationship　between　the　top　side　weld　pool　characterized　parameters　and　the　backside　weld　pool　width.　With　the　proposed　methods,　the　validity　and　reliability　of　the　topside　weld　pool　characteristic　parameters　were　verified.　The　methods　and　results　of　these　modeling　and　simulation　provide　the　conditions　for　exploring　the　welding　shape　rules　and　designing　the　welding　process　controllers.