Following polymerization, impurities composed of adduct, used solvent and catalyst remain inside the formed polymers. These aforementioned impurities should be removed by washing to improve the purity of the polymers. In this process, a model of the polymer washing process is essential for optimizing energy, resources and operating time. This study proposes a fundamental model of a polymer washing process to provide a theoretical basis for optimization. This model describes the impurity distribution inside the polymers using the pseudo-steady-state approximation with the concept of a moving boundary of diffusion. The impurity diffusion at the polymer surface is described using Fick's law. In addition, this work reports an experimental investigation of a polymer washing process using SPAEK (sulfonated poly(aryl ether ketone)) samples. The obtained pH data are used to compute the impurity diffusion coefficient at the polymer surface. Although the computed diffusion coefficients themselves show different values for each operation as a lumped parameter, the introduction of a dimensionless number, Co, scaled by the initial concentrations for each operation, yields the same values for each operation. This result implies that the unmodeled effects that might affect the impurity diffusion are only affected by Co, even if the initial impurity concentrations inside the polymers are different for each operation. Finally, the predicted pH changes under different experimental conditions showed that the model describes the washing process well and can be applied to the process design and optimization.