Camera calibration is essential for any optical system used to obtain 3D measurements from images. The precision of the 3D depth estimation relies on an appropriate camera model and the accurate estimation of model parameters. These parameters are sensitive to environmental conditions and it is well established that a vision system should be calibrated in operating conditions. This is not always possible since the calibration process is often tedious and time-consuming. Unfortunately, the use of poorly estimated calibration parameters for 3D reconstruction and measurements may lead to suboptimal performance of the system and inaccurate depth estimation. This paper presents a technique using an existing camera model and optical design software to perform calibration simulations. This virtual calibration technique allows for a study of the impact of environmental conditions on the calibration parameters. Using this procedure, it is also possible to predict the statistical behavior of the calibration parameters considering the chosen fabrication processes and tolerances. It can assist vision scientists in the choice of the optical system that best meets the requested precision of the 3D reconstruction. This technique could eventually be integrated in the lens design process to create more reliable optical systems that could be calibrated and used in a range of environmental conditions with a very small variation of their calibration parameters.