System Dynamics (SD) is a special type of simulation modeling where output validity refers to validating the patterns of dynamic behaviors, such as oscillations, growth or decline. The developers and users of these models (the decision makers and people affected by decisions based on such models) are all rightly concerned with whether a model and its results are “valid.” Structural model validity and validation have long been recognized as one of the main issues in system dynamics. This concern is addressed through pattern recognition and testing in this paper. Another issue in dynamic simulation methodology is parameter calibration; assuming that the structure of simulation model constructed by the user is valid. Parameter calibration is the minimization of an error function which is a measure of the correspondence between numerically calculated output patterns and the respective real behavior patterns. We offer a software that does automated parameter calibration with respect to a given (desired) dynamic pattern. This particular feature can also be used in policy improvement design.