The difficulty associated with accurately measuring the height of the back peak (Ipb) in cyclic voltammetry (CV) has long plagued electrochemists. Most commonly, Ipb is measured by extrapolating a linear fit from a selected region of a voltammogram after the switching potential (Eλ), but without substantial separation between the peak potential (Ep) and Eλ, this approach always overestimates the background current and so underestimates Ipb. Moreover, experimental conditions can present challenges for this method as an appropriate region for linear fitting is often lacking due to neighboring peaks or solvent electrolysis current. Here, we present a new method for finding the baseline current for the back peak in CV experiments. By examining the CV data as a function of time rather than potential, it is possible to fit a generalized Cottrell or Shoup-Szabo equation to the current decay of the forward peak and extrapolate this function as a baseline for the return peak. This approach was tested by using simulated and experimental data in a variety of conditions, including data demonstrating linear and radial diffusional control. We found that the method allows for more accurate determination of back peak currents, especially when linear fits are complicated by narrow electrochemical windows or radial diffusion. A user-friendly Python program was written to automatically find an appropriate fitting range for this analysis and measure peak currents. We have made this program available to the electrochemical community at large.