I use one of the common scientific data analysis applications, Wavemetrics Igor Pro. Self-explanatory
I estimated the drag coefficients by comparing freefall data with standard geometric drag models. There are numerous data sets from flights where the motors were stopped or props were lost - that's the freefall data. There are also accepted drag coefficient equations for various geometric shapes. I used a combination of those to get the drag coefficients.
It's highly simplified in its assumption of isotropic behavior, but it seems to be close enough to predict trajectories with a somewhat useful level of fidelity. The model assumes that the drag coefficient is constant - independent of the orientation of the aircraft (isotropic). That's obviously not going to be fully correct, but works well enough.
Even with the simplest drag model included there is no analytic solution to the resulting differential equations of motion, and so those are solved with a first order numerical finite difference method. The differential equations of motion (in the form of F = ma - Newton's 2nd law) form cannot simply be rearranged and integrated to get velocity and position as a function of time (an analytic solution), and so an iterative, time-stepping (explicit) numerical method has to be used instead.
Unfortunately such methods require a reasonable level of comfort with at least college level physics and mathematics as well as somewhat costly software, and so I suspect that the audience for such a thing would be very small indeed. The methods are not easily understood by the layman.
. And agree with others - 
