In addition to the thermal comfort of the vehicle occupants, their safety by ensuring adequate visibility is an objective of the automotive climate control system. An integrated dew point and glass temperature sensor is widely used among several other technologies to detect risk of fog formation on the cabin side (or inner) surface of the windshield. The erroneous information from a sensor such as the measurement lag can cause imperfect visibility due to the delayed response of the climate control system. Also the high value, low cost vehicles may not have this sensor due to its high cost. A differential equation based model of the cabin air humidity is proposed to calculate in real-time specific humidity of the passenger compartment air. The specific humidity is used along with the windshield surface temperature to determine relative humidity of air and therefore, the risk of fog formation on the interior surface of a windshield. The generally uniform spatial distribution of cabin air humidity is used to advantage. However, the accuracy of a cabin air humidity model is evaluated for the non-uniform distribution of the windshield surface temperature and the uncertainty of the parameters of a differential equation model. The sensitivity analysis is performed to determine acceptable range of each parameter for an accurate prediction of fog or frost formation on the windshield surface. Application of a cabin air humidity model to predict risk of fog formation is demonstrated with an experimental vehicle installed with three humidity - integrated dew point and glass temperature sensors. The implication of the use of a model for diagnosis of a humidity sensor is also outlined.