The aim of this study was to develop a functional model of monofin swimming by assigning numerical forms to certain technique parameters. The precise determination of optimal foot displacement and monofin strain points toward a model aspect for increasing swimming speed. Eleven professional swimmers were filmed underwater. The kinematic data were then used as entry variable for an artificial neural network, which itself created the foundation for a model of monofin swimming technique. The resulting network response graphs indicate a division set of standard deviation values in which the examined angular parameters of foot and monofin displacement achieve optimal values in terms of gaining maximal swimming speed. During the upward movement, it is essential to limit dorsal foot flexion (-20) from the parallel position toward the shin (180 degrees). During the downward movement, plantar flexion should not exceed 180 degrees. The optimal scope of the proximal part of the fin strain is 35 degrees in the downward move ment and (-)27 degrees in the upward; the angles of attack of the distal part of the fin and its entire surface are limited to 37 degrees in the downward movement and (-)26 degrees in the upward. Optimization criteria allowed for movement modification to gain and maintain maximal velocity during both cycle phases and to limit cycle velocity decrease.