Paired-pulse stimulation is a standard protocol that has been used for decades to characterize dynamic systems: the differences in responses to two sequential identical stimuli as a function of inter-stimulus interval provide quantitative information on the dynamics of the system. In neuroscience, the paired-pulse protocol is also widely used at multiple levels of analysis, from behavioral conditioning to synaptic plasticity, and in particular to define the biomolecular mechanism of learning and memory. In a system as small and complex as synapses, it is extremely challenging - if not impossible - to experimentally gain access to the multitude of possible readouts. In the present study, we first introduce a computational synaptic modeling platform that we developed and calibrated based on experimental data from both our laboratories and a variety of publications. We then show how this platform allows not only to replicate experimental data, but also to go beyond technological boundaries and investigate the main parameters responsible for regulation of synaptic transmission and plasticity. The results provide critical information regarding the respective role of various subsynaptic processes and of their interactions. Additionally, this approach can strengthen our understanding of potential dysfunctions (pathologies) and suggest potential approaches to re-establish normal function.