<p>An approach is proposed to model uncertainty in a process by combining classical and quantum computing. The model of the process differs from a traditional stochastic process due to the prospect of using quantum superposition and entanglement for quantifying the uncertainty present. The model of the stochastic noise is developed based on multidimensional Hadamard gates which can be also implemented in terms of quantum Fourier transform (QFT). The process of degradation of quality of air filters used for environmental control in transportation systems is modeled and the application of the developed model is demonstrated with real-world data for transportation systems. The versatility of the combined classical–quantum uncertainty model is testified by several numerical experiments conducted under different conditions and prediction horizons. Additional models of uncertainty are developed with the introduction of rotational gates in the quantum circuits. End of life of air filters is predicted using the proposed classical–quantum analysis. The results show that the proposed approach is capable of predicting the uncertainty in the future behavior of the air filters and of capturing the inherent fluctuations within the process. The advantage in time complexity compared to classical computation is also evaluated and discussed.</p>