Detailed neuron models consisting of thousands of synapses are key for understanding the computational properties of single neurons and large neuronal networks, and for interpreting experimental results. Simulations of these models are however, computationally expensive (using lots of computing hours), which considerably decreases their utility. Scientists at the Hebrew University of Jerusalem and the EPFL Blue Brain Project have formulated a unique analytical approach to the challenge of reducing the complexity of neuron models while retaining their key input/ output functions and their computational capabilities. ‘Neuron_Reduce’ is a new computational tool that provides the scientific community with a straightforward capability to simplify complex neuron models of any cell type and still faithfully preserve its input-output properties while significantly reducing simulation run-time.