We have developed a model for the variability of spore lag times and shown that variability has an important role in the quantitative assessment of risks associated with spore forming bacteria in food. The model includes two sequential independent delay times that contribute to the lag time for a single spore. We have shown that a population of variable spores also has a variable lag time, and we have emphasised the significance of this variability in quantitative representations of population dynamics for small populations. We have made a Bayesian estimate for the extent of the variability in spore lag times and made a comparison with direct microscopic observations of individual spores of nonproteolytic Clostridium botulinum. We conclude that Bayesian inference is a practical method for quantifying variability and hence a significant element in the development of quantitative risk assessments for hazards associated with spore forming bacteria.