In chemical synapses of the central nervous system (CNS), information is transmitted via the presynaptic release of a vesicle (or ‘quantum’) of neurotransmitter, which elicits a postsynaptic electrical response with an amplitude termed the ‘quantal size’. This key determinant of neural computation is hard to measure reliably due to its small size and the multiple sources of noise within neurons and electrophysiological recordings. Measuring amplitudes of miniature postsynaptic currents (mPSCs) or potentials (mPSPs) at the cell soma potentially offers a technically straightforward way to estimate quantal sizes, as each of these miniature responses (or ‘minis’) is elicited by the spontaneous release of a single neurotransmitter vesicle. However, a somatically recorded mini is typically massively attenuated compared with at its input site, and a significant fraction are indistinguishable from (or cancelled out by) background noise fluctuations. Here we describe a novel quantal analysis method that estimates electrical size of the synapse by combining separate somatic recordings of background physiological noise and minis with simulations. With the help of a genetic algorithm, simulations are successfully used to infer the combined amplitude and rise time distribution of minis that would otherwise be inaccessible due to low signal to noise ratio. The estimated distributions reveal a striking inverse dependence of mean minis’ amplitudes on cell’s total capacitance (a proxy for the size of cells) that firmly supports the conservation of the electrical size of excitatory cortical synapses in rats. We incorporate the novel quantal analysis method into our patch clamp data analysis software called ‘minis’.