Motivated by the need for an efficient fatigue crack growth prediction infrastructure for both legacy and novel materials, we have initiated the development of an automated computational framework capable of determining crack growth model parameters for an equationally defined model. As a first step in addressing this need, the present paper focuses on the Hartman-Schijve crack growth variant of the NASGRO equation by exploring and comparing various global optimization methods for parameter determination and evaluating their performance by using both synthetic and actual data. It also introduces the concept of the total least-squares minimization criterion within the context of crack growth modeling. The development of an open-source software library and an application implementing the approach are also described and are available for distribution to the technical community.