Estimation of human attentional states using an electroencephalogram (EEG) has been demonstrated to help prevent human errors associated with the degradation. Since the use of the lambda response -one of eye-fixation-related potentials time-locked to the saccade offset- enables such estimation without external triggers, the measurements are compatible for an application in a real-world environment. With aiming to apply the lambda response as an index of human errors during the visual inspection, the current research elucidated whether the mean amplitude of the lambda response was a predictor of the number of inspection errors. EEGs were measured from 50 participants while inspecting the differences between two images of the circuit board. Twenty percent of the total number of image pairs included differences. The lambda response was obtained relative to a saccade offset starting a fixation of the inspection image. Participants conducted four sessions over two days (625 trials/ session, 2 sessions/ day). A Poisson regression of the number of inspection errors using a generalized linear mixed model showed that a coefficient of the mean amplitude of the lambda response was significant , suggesting that the response has a role in th$(\hat \beta = 0.24,p < 0.01)$e prediction of the number of human error occurrences in the visual inspection.