The paper presents a numerical analysis of the coupled heat and mass transfer phenomena in macroscopic terms during the cryopreservation of biological tissue. The research takes into account imprecise parameters present in the mathematical model. In general, transport phenomena occurring in biological materials during cryopreservation often include uncertainly defined quantities. This is because the model parameters are determined by experiments, and the measurements depend, for example, on the condition or age of the organism used to extract the sample. Imprecise variables can be estimated applying probabilistic or non-probabilistic methods. The probabilistic approach relies on stochastic algorithms, which can sometimes prove ineffective due to limited access to measurement data. On the other hand, non-probabilistic methods include fuzzy set theory and interval set theory. The subject of the study is the implementation of non-probabilistic algorithms, more specifically, the theories of interval sets and fuzzy sets to a numerical model describing transport phenomena during cryopreservation in the macro scale. Thermal analysis is performed using the Fourier equation, while the mass transfer is calculated using the diffusion equation based on Fick's second law. These phenomena are coupled by the diffusion coefficient, which depends on the temperature in the computational domain. The final part of the paper focuses on comparing the results for interval numbers and fuzzy numbers characterised by different membership functions. The results obtained are compared with the data found in the literature.