The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has resulted in a global pandemic that demands urgent abatement solutions. Remdesivir (RDV) has been used as a compassionate-use-drug for managing COVID-19 patients and approved by FDA, yet the clinical performances of RDV were controversial. In addition, pharmacokinetic data have not sufficiently collected from different age groups and those with underlying diseases. In this work, we have developed a pharmacokinetic (PK) model for RDV, at first based on the PK data collected from monkeys, and then extrapolated to human beings. The model consists of four ordinary differential equations which represents the metabolic pathways i.e. from RDV to intermediate metabolites, and finally to the antiviral nucleosides triphosphate (NTP). We used two methods to estimate the parameters in the model: (1) nonlinear regression analysis; (2) Latin Hypercube Sampling analysis. We show that with the model we are able to reproduce the PK profiles of RDV and NTP, which have been made available from a few pilot studies (e.g. the PK study of RDV for treating Ebola virus, and the clinical data published by Gilead the drug’s producer). The model lends itself to further modifications, when data concerning age, gender, and underlying disease differences become available. In conclusion we have developed a simple mathematical model for remdesivir. The model may benefit future population PK related studies of this drug.