After the nuclear accident at the Fukushima Daiichi nuclear power plant, hydrogen generation has resurfaced as a key issue, with respect to its quantification in the simulation of severe accidents, because of the potential risk of deflagration or detonation, which would compromise the integrity of the plant facilities. Severe accident simulation codes may have different models to predict cladding oxidation rates and the consequent hydrogen generation. Thus, sensitivity and uncertainty analysis can be applied to determine which code input variables have a significant impact in the implemented models, and consequently on the overall predicted values of key figures of merit. In this work, the generation of hydrogen in the reactor core during a short-term station blackout is studied as a figure of merit for a BWR. The scope of the analysis is until the failure of the reactor pressure vessel. This study shows a sensitivity and uncertainty analysis through the complementary calculations of two methods: Chi-squared parameter and Pearson simple correlation coefficient. The severe accident simulation code was MAAP 5.0.3 and the AZTUSIA code was used as the statistical tool for the sensitivity and uncertainty analysis. Ten uncertain parameters were chosen, of which two are MAAP models options, and the values were generated via the simple random Monte Carlo technique. The results show that the Chi-square parameter in conjunction with correlation coefficients provides a more comprehensive understanding of the impact of both quantitative and qualitative input variables on the figures of merit.