Conductance-based neuron models aid in understanding the role intrinsic and synaptic currents play in producing neuronal activity. Incorporating morphological detail into a model allows for additional analysis of non-homogeneous distributions of active and synaptic conductances, as well as spatial segregation of electrical events. We developed a morphologically detailed "Full Model" of a leech heart interneuron that replicates reasonably well intracellular recordings from these interneurons. However, it comprises hundreds of compartments, each increasing parameter space and simulation time. To reduce the number of compartments of the Full Model, while preserving conductance densities and distributions, its compartments were grouped into functional groups that each share identical conductance densities. Each functional group was sequentially reduced to one or two compartments, preserving surface area, conductance densities and its contribution to input resistance. As a result, the input resistance and membrane time constant were preserved. The axial resistances of several compartments were rescaled to match the amplitude of synaptic currents and low-threshold calcium currents and the shape of action potentials to those in the Full Model. This reduced model, with intrinsic conductances, matched the activity of the Full Model for a variety of simulated current-clamp and voltage-clamp data. Because surface area and conductance distribution of the functional regions of the Full Model were maintained, parameter changes introduced into the reduced model can be directly translated to the Full Model. Thus, our computationally efficient reduced morphology model can be used as a tool for exploring the parameter space of the Full Model and in network simulations.