Human　reliability　analysis　(HRA)　is　a　proactive　approach　to　model　and　evaluate　systematic　human　errors　and　has　been　extensively　implemented　in　various　complicated　systems.　The　assessment　of　human　errors　relies　heavily　on　the　knowledge　and　experience　of　experts　in　real-world　cases.　Moreover,　there　are　usually　specific　sorts　of　uncertainty　while　experts　use　linguistic　labels　to　evaluate　human　failure　events.　In　this　context,　this　paper　seeks　to　establish　a　new　model　based　on　the　hesitant　fuzzy　matrix　(HFM)　and　the　cognitive　reliability　and　error　analysis　method　(CREAM)　to　conduct　a　quantitative　analysis　of　human　errors.　This　model　handles　the　multiple　crisp　scores　of　the　common　performance　conditions　(CPCs)　given　by　experts　according　to　the　context　description　in　terms　of　CPCs,　determines　the　weights　of　CPCs　by　the　HFM,　and　elicits　the　human　error　probability　(HEP)　point　estimation　formula　considering　consequences　based　on　the　CREAM.　Finally,　the　effectiveness　and　practicality　of　the　presented　HFM-CREAM　model　are　demonstrated　through　the　emergency　response　analysis　of　the　steam　generator　tube　rupture　(SGTR)　in　nuclear　power　plant.