Portion size estimation is expected to be one of the largest sources of uncertainty in dietary assessment of the individual. Therefore, we demonstrated a method to quantify uncertainty due to portion size estimation in the usual intake distributions of vegetables, fruit, bread, protein, and potassium. Dutch participants of the European Food Consumption Validation study completed 2 nonconsecutive 24-h recall interviews. In short, the uncertainty analysis consists of Monte Carlo simulations drawing values for portion size from lognormal uncertainty distributions. The uncertainty of the usual intake distribution and accompanying parameters (IQR and the shrinkage factor) were estimated. For the food groups, portion size uncertainty had the greatest effect for vegetables and the least for fruit: the relative 95% uncertainty interval (UI) of the IQR of the usual intake distribution was 0.61–1.35 for vegetables, 0.77–1.24 for bread, and 0.99–1.10 for fruit. For protein and potassium, the resulting relative width of the UI of the IQR for portion size uncertainty are similar: 0.88–1.14 for protein and 0.86–1.14 for potassium. Furthermore, a sensitivity analysis illustrated the importance of the specified uncertainty distributions. The examples show that uncertainty in portion sizes may be more important for some foods such as vegetables. This may reflect differential quantification errors by food groups that deserve further consideration. In conclusion, the presented methodology allows the important quantification of portion size uncertainty and extensions to include other sources of uncertainty is straightforward.