Quality control seeks to collect and analyze large amounts of data to take appropriate corrective actions and ensure that products or services meet quality requirements. This study proposed a methodological framework to analyze the quality control process employing Monte Carlo simulation. The methodology consists of four steps: (i) Establishment of probability distributions, (ii) Construction of the mathematical model, (iii) Running the simulation, and (iv) Analysis of the results. The application of the methodological framework in a carbonated beverage production made it possible to ensure with 99% confidence that one of the most important quality characteristics of the product, the degrees Brix, varies in a range of ± 0.02. The results show the methodology allows to broadly map the process variables behavior and to make decisions on optimal levels for quality monitoring and control.