Abstract: Background: This study analysed determinants of vulnerability to poverty in South Africa utilising the General Household Surveys from 201 2 to 2015. Data source and methods: The Foster Greere Thorbecl‹e poverty index by groups and income components using the Shapley Value was used to identify household vulnerability status. A multinomial logit model was used to investigate factors that contribute to vulnerability to poverty. Results: The study findings pointed out that high-income variability contributes to vulnerability and poverty among urban and rural areas. Additionally, the findings of the study demonstrated that only a few households fall in the middle (lower bound) poverty lines. Conclusions: Race and location are strong predictors of poverty in South Africa. Keywords: Income distribution, Inequality, Multinomial logit model, Principal Component, sub-Sahara JEL Classification C2 I C6 1 1320 10 R20