This paper systematically evaluates the effect of some methodological or assumptions on the robustness of Vulnerability to Food Insecurity Index. The focus was to examine how data type, weight scheme, normalisation method and exclusion/inclusion of variable affect the model of the index using uncertainty and sensitivity analysis. The paper used two approaches: One-at-a-time and global sensitivity approach for the analysis. Using one-at-a-time approach, we explore how the VFII output response to different weighting scheme, normalisation method and inclusion/exclusion of variable. For the global approach, we used Sobol’ first-order index and total effect index to explore the uncertainty and sensitivity of VFII. The result of the robustness analysis indicated that VFII performance is stable to changes in the variables and normalisation method when equal weight is applied. Using the min-max normalisation method produces a highly robust estimate. The shock variable was the primary input factor that influences the variation in the output of the VFII. This implies that the VFII is highly sensitive to shocks, therefore better capturing the vulnerability component of food security.