The variability effect of kinetic data was investigated by simulating orange juice pectinmethylesterase (PME) inactivation with combined processes of high hydrostatic pressure-temperature (100-500 MPa; 20-40°C), applying the Monte Carlo method. Parameters from an Eyring-Arrheniius model that predicts the kinetic inactivation constant (k) as a function of both pressure and temperature were found reported in literature and considered for the analysis. The kinetic analysis was carried out with both Monte Carlo simulations and the traditional deterministic approach, which only considers mean values and does not take into account data variability. Simulations with the Monte Carlo method demonstrated that residual PME activity predicted with deterministic calculations greatly differed from those obtained through confidence intervals of simulated probabilistic distributions. Mean values overrated residual enzyme activity from 4% to ≈ 2,800% when compared to the 95% confidence intervals generated with the Monte Carlo method. This divergence augmented as both applied pressure and temperature levels increased. Similar risk analysis projects can be further developed to establish the foundations for future food processing regulations of enzymatic control.