An object surface correction method for predicting whether a shape of an object surface can be recognized by the human eye and correcting the object surface based on the prediction, comprising: preparing a test piece, actually measuring, for the surface of the test piece, a machining shape, a surface roughness curve, a viewpoint position, direction and intensity of incident light on the surface of the test piece and the reflectance and scattering characteristics of each wavelength of light incident on the surface of the test piece, repeatedly predicting and displaying the shape of the surface of the test piece while changing the angular distribution of the incident light based on data related to the actually measured machining shape, surface roughness curve, viewpoint position, direction and intensity of incident light on the surface of the test piece and the reflectance and scattering characteristics of each wavelength of light incident on the surface of the test piece, and calibrating the angular distribution of the incident light on the surface of the test piece so that the displayed surface shape of the test piece matches the surface shape of the test piece as visually observed by an observer, dividing the object surface, which is to be machined by a machine tool, into a plurality of regions, calculating, for each of the plurality of regions, a luminance of the object surface when the object surface is observed from the viewpoint position based on the shape of the object to be machined, the surface roughness curve, the viewpoint position, the incident light, and the reflected light, predicting, based on the calculated luminance, whether the shape of the object surface can be recognized by the human eye, and correcting, based on the predicted shape of the object surface, the data related to at least one of the shape of the object to be machined by the machine tool and surface roughness curve of the object so as to obtain a desired aesthetic of the object surface. preparing a test piece, actually measuring, for the surface of the test piece, a machining shape, a surface roughness curve, a viewpoint position, direction and intensity of incident light on the surface of the test piece and the reflectance and scattering characteristics of each wavelength of light incident on the surface of the test piece, repeatedly predicting and displaying the shape of the surface of the test piece while changing the angular distribution of the incident light based on data related to the actually measured machining shape, surface roughness curve, viewpoint position, direction and intensity of incident light on the surface of the test piece and the reflectance and scattering characteristics of each wavelength of light incident on the surface of the test piece, and calibrating the angular distribution of the incident light on the surface of the test piece so that the displayed surface shape of the test piece matches the surface shape of the test piece as visually observed by an observer, dividing the object surface, which is to be machined by a machine tool, into a plurality of regions, calculating, for each of the plurality of regions, a luminance of the object surface when the object surface is observed from the viewpoint position based on the shape of the object to be machined, the surface roughness curve, the viewpoint position, the incident light, and the reflected light, predicting, based on the calculated luminance, whether the shape of the object surface can be recognized by the human eye, and correcting, based on the predicted shape of the object surface, the data related to at least one of the shape of the object to be machined by the machine tool and surface roughness curve of the object so as to obtain a desired aesthetic of the object surface.