In　this　paper,　a　probability　optimization　approach　for　economic　performance　assessment　of　the　constrained　process　control　under　uncertainty　is　presented.　Performance　evaluation　problems　are　formulated　as　the　stochastic　problems　which　incorporate　the　uncertainties　in　both　process　operation　and　economic　objective.　Such　problem　formulation　helps　to　identify　the　opportunity　of　improving　the　profitability　of　the　process　by　taking　appropriate　risks.　Both　the　steady　state　economic　benefit　and　the　optimal　operation　conditions　can　be　obtained　by　solving　the　defined　economic　optimization　problems.　Further,　the　proposed　method　uses　the　LQG　benchmark　other　than　conventional　minimum　variance　control　(MVC)　benchmark　to　estimate　potential　of　variance　reduction,　which　results　in　a　more　reasonable　performance　assessment.　The　proposed　algorithm　is　also　illustrated　by　a　simulated　example　of　the　model　predictive　control　system.　©　2011　Zhejiang　University.