Background and objective: Transdermal delivery of a therapeutic drug is a non-invasive method of drug administration. For a controlled delivery of the maximum number of drugs, several external enhancement mechanisms are used in the domain of transdermal drug delivery (TDD). Iontophoresis is one of the processes which uses a weak electric current to increase drug delivery and electrically control its penetration into the body. This method is governed by the Nernst-Planck equation, which gives the total flux of administering drugs due to iontophoresis. In this work, an effort has been made to simulate iontophoresis to predict transdermal drugs in the dermal layers using electrical equivalent skin models.Methods: As the executable route of drug administration is skin, the electrical impedance value of the dermal layers can be utilized in predicting the amount of iontophoretic drug flux by introducing impedance parameters of skin in the Nernst-Planck equation. Researchers have developed electrical equivalent models of skin that explain the skin’s physiological stratification and biological properties.Results: Numerical simulation of iontophoresis is performed using the human skin impedance values with these impedance models of skin to predict drug concentrations in the dermal layers. For the computation and analysis of drug delivery using simulations, boundary conditions were developed based on the descriptions of the electrical impedance models and the morphology of human skin.Conclusions: This proposed method establishes a clear relationship between TDD and skin impedance. It could be used in in-silico prediction before experimentation of any drugs on live animals or humans. The adopted methodology could be implemented in programming to develop software for real-time prediction of transdermal drugs in dermal layers using instantaneous skin impedance values. Further researchers can work upon this idea to include more natural constraints that identify complex biological features of the skin and physio-chemical properties of drugs.