Locomotion is crucial for an animal’s survival. Despite its importance, our understanding of how movement is generated is limited. Zebrafish (Danio rerio) is a commonly used animal to study the spinal control of movement. Many neuronal populations found in zebrafish are evolutionarily conserved across species, including mammals. Even as early as 4-5 days post fertilization, larval zebrafish display a wide range of swimming speeds measured in tail beat frequencies, making it a great model to study locomotor control. Experimental studies have identified several populations of spinal neurons composing microcircuits dedicated to specific ranges of swimming speed of zebrafish. How these microcircuits function remains to be determined. We developed a software tool, SiliFish, to allow the generation of complex and realistic computational models to emulate spinal control of motor movements. We implemented features that facilitate generating the intrinsic and extrinsic properties observed experimentally. Using the data from the literature to constrain our models, we generated a model of larval zebrafish spinal cord consisting of neuronal pools that are differentially recruited, generating a wide range of tail beat frequencies, forming the slow, intermediate and fast swim circuits. We were also able to replicate some of the experimental manipulations to confirm the validity of the models.