Plug-in　connector　of　gas　insulated　bus　(GIB)　could　be　subject　to　the　wear　and　electrical　contact　resistance　(ECR)　deterioration　processes　under　cyclic　mechanical　and　current　loads.　A　specific　test　platform　is　designed　to　simulate　the　current-carrying　wear　and　ECR　degradation　process　of　Ag-plated　GIB　electrical　contact　spot　inside　SF6,　N2　and　Air　insulation　mediums　under　current　loads.　Worn　surface　morphology　and　chemical　composition　are　observed　and　analyzed.　Influence　of　insulation　medium　and　current　load　on　deterioration　mechanism　of　GIB　electrical　contact　are　discussed.　Raw　ECR　curve　obtained　from　current-carrying　experiment　is　smoothed　by　the　exponentially　weighted　moving　average　(EWMA)　method.　A　long　short-term　memory　(LSTM)　neural　network　is　then　proposed　to　realize　both　single-step　and　multi-step　ECR　and　failure　predictions　of　GIB　electrical　contact.　Results　show　that　adhesive　wear　on　contact　surface　happened　due　to　materials　transfer.　Deterioration　of　contact　spot　inside　air　medium　is　much　severer　than　those　in　SF6　and　N2　due　to　oxidation　effect.　Deterioration　of　contact　spot　inside　SF6　medium　under　high　current　load　is　severer　than　those　under　low　current　load　due　to　the　change　of　wear　behavior　and　chemical　reactions.　Compared　with　other　methods,　LSTM　could　achieve　better　performance　in　both　single-step　and　multi-step　failure　prediction　of　GIB　electrical　contact.