Simulating the effects of skincare products on the face is a potential new mode for product self-promotion while facilitating consumers to choose the right product. Furthermore, such simulations enable one to anticipate her skin condition and better manage skin health. However, there is a lack of effective simulations today. In this paper, we propose the first simulation model to reveal facial pore changes after using skincare products. Our simulation pipeline consists of two steps: training data establishment and facial pore simulation. To establish training data, we collect face images with various pore quality indexes from short-term (8-weeks) clinical studies. People experience significant skin fluctuations (due to natural rhythms, external stressors, etc.,) which introduce large perturbations, and we propose a sliding window mechanism to clean data and select representative index(es) to present facial pore changes. The facial pore simulation stage consists of 3 modules: UNet-based segmentation module to localize facial pores; regression module to predict time-dependent warping hyperparameters; and deformation module, taking warping hyperparameters and pore segmentation labels as inputs, to precisely deform pores accordingly. The proposed simulation renders realistic facial pore changes. This work will pave the way for future research in facial skin simulation and skincare product developments.