This　paper　studies　the　competitiveness　of　listed　companies　in　high-end　equipment　manufacturing　industry　by　using　random　forest.　Random　forest　is　a　supervised　machine　learning　algorithm　that　is　actually　based　on　the　regression　and　classification.　It　takes　some　important　decisions　that　are　always　based　upon　the　set　of　samples.　It　counts　majority　for　the　classification　purposes　while　it　takes　an　average　for　the　regression.　For　empirical　analysis,　88　listed　companies　are　selected.　It　is　found　that　there　are　great　differences　in　comprehensive　competitiveness　among　industries.　Enterprise　scale　accounts　for　a　high　proportion　in　the　comprehensive　competitiveness,　and　its　score　often　affects　the　comprehensive　strength;　and　the　gap　between　companies　in　the　same　industry　is　also　obvious.　The　empirical　evaluation　results　of　this　paper　provide　three　enlightenments　for　enterprises　to　improve　their　comprehensive　competitiveness,　such　as　seizing　the　strategic　opportunity　to　expand　the　market,　expand　the　scale　of　enterprises,　improve　asset　management,　and　narrow　the　industry　gap.