Recently a number of attempts have been made to validate and calibrate power system cascading failure simulation models. The objective of this paper is to assess the potential for model calibration. For that purpose, we propose a generic framework for the calibration of cascading failure analysis models. The framework is based on tuning the optimal values of model parameters, i.e. line/transformer tripping power-flow thresholds, which are usually diverse depending on the particular settings chosen by maintenance personnel. The framework application is exemplified by calibrating the parameters of a cascading failure model based on DC power flow (PF). The parameters are optimized through minimizing the difference between the probability distributions of historical blackout data and of the simulation results for the same electric power transmission system. The problem is casted as single-objective optimization and is solved using different optimization techniques. The efficiency of the proposed framework and the selected optimization techniques is demonstrated on the Western Electricity Coordinating Council (WECC) power transmission system. The obtained results show that by tuning model parameters optimally, one can achieve a good agreement between the simulation results and the historical data. These findings support the applicability of the cascading failure simulations to power system risk assessment.