A growing body of literature points to the importance of the explicit parameterization of neural power spectra for the appropriate physiological interpretation of periodic and aperiodic electroencephalogram (EEG) activity. In this paper, we discuss why parameterization is an imperative step for developmental cognitive neuroscientists interested in cognition and behavior across the lifespan, as well as how this can be readily accomplished with an automated spectral parameterization (“specparam”) algorithm (Donoghue et al., 2020a). We provide annotated code for power spectral parameterization, via specparam, in Jupyter Notebook and R Studio. We then apply this algorithm to EEG data in childhood (N = 60; Mage = 10.80, SD = 1.00) to illustrate its utility for developmental cognitive neuroscientists. Ultimately, explicit parameterization of neural power spectra may help us refine our understanding of how dynamic neural communication contributes to normative and aberrant cognition across the lifespan. Data and annotated analysis code for this manuscript are available on GitHub (https://github.com/fooof-tools/DevDemo) as a supplement to the open-access specparam toolbox (https://fooof-tools.github.io/).