The　robustness　of　adversarial　examples　to　image　scaling　transformation　is　usually　ignored　when　most　existing　adversarial　attacks　are　proposed.In　con-trast,image　scaling　is　often　the　first　step　of　the　model　to　transfer　various　sizes　of　input　images　into　fixed　ones.We　evaluate　the　impact　of　image　scaling　on　the　robustness　of　adversarial　examples　applied　to　image　classification　tasks.We　set　up　an　image　scaling　system　to　provide　a　basis　for　robustness　evaluation　and　conduct　experiments　in　differ-ent　situations　to　explore　the　relationship　between　image　scaling　and　the　robustness　of　adversarial　examples.Exper-iment　results　show　that　various　scaling　algorithms　have　a　similar　impact　on　the　robustness　of　adversarial　examples,but　the　scaling　ratio　significantly　impacts　it.