This study is aimed to identify latent classes which are based the change patterns of employment status of people with visual impairments and to test the effects of independent variables(gender, age, disability density, disability status, spouse, education, license, employment service, number of household members, income of househol, livelihood protection) on determining latents classes. The disabled panel(1-6 round) data established by Korea Employment Agency for the Disabled(KEAD) was used for analyzing. Nagin's(1999) semi-parametric group based approach was applied and because dependant variable has dichotomous scale, logit model was used for estimating latent classes. The results identified four latent classes, which could be defined based on the patterns as follows; economically inactive group, group with low possibility of employment, group with low probability of employment, employment maintenance group. The effects of the independent variables on the latent classes was tested by multinomial logit analysis. The results showed that gender, age, disability degree, health condition, spouse, employment service, number of household members, household income, livelihood protection were significant determinants of the latent classes. Finally, the implications based on analysis results were suggested.