We presented a probabilistic framework considering sensitivity analysis, calibration and uncertainty quantification applied on heavy oil estimations with a corresponding states model (CSP). This approach provides new information when compared with classic deterministic methods (for instance, Least-Squares meth-ods), such as regions where the prediction is not reliable as well as which parts the range of uncertainties are wider. This way, additional knowledge of the analyzed CSP viscosity model is obtained concerning the applicability context in the light of statistical violations. Moreover, the non-intrusive sensitivity analysis method of Elementary Effects was employed to determine the most influential fitting parameters. With such information, parameters which do not effectively contribute to model calibration are neglected in this stage, decreasing time computational costs and enhancing calibration performance. The results clarified the limitations of CSP viscosity model applied to heavy oil samples, indicating that for low pressure and mid temperature conditions, the model can be inappropriate. The presented unified approach has potential to be automatically applied on data from viscosity experiment reports, avoiding the necessity to perform trials-and-errors strategy to fit the model and choose which parameters must be calibrated. fluids from their compositions. Journal of Petroleum Technology 1964, 16, 1-171.