In　recent　years,　Kriging　model　has　gained　wide　popularity　in　various　fields　such　as　space　geology,　econometrics,　and　computer　experiments.　As　a　result,　research　on　this　model　has　proliferated.　In　this　paper,　the　authors　propose　a　model　averaging　estimation　based　on　the　best　linear　unbiased　prediction　of　Kriging　model　and　the　leave-one-out　cross-validation　method,　with　consideration　for　the　model　uncertainty.　The　authors　present　a　weight　selection　criterion　for　the　model　averaging　estimation　and　provide　two　theoretical　justifications　for　the　proposed　method.　First,　the　estimated　weight　based　on　the　proposed　criterion　is　asymptotically　optimal　in　achieving　the　lowest　possible　prediction　risk.　Second,　the　proposed　method　asymptotically　assigns　all　weights　to　the　correctly　specified　models　when　the　candidate　model　set　includes　these　models.　The　effectiveness　of　the　proposed　method　is　verified　through　numerical　analyses.