The aim of this investigation was to test the predictive power of the dynamic stiffness measurement to identify eggs which are most likely to crack under field conditions. A representative sample of eggs (n = 1660) was collected from the front of the cages in a commercial battery unit. Egg weight,% damping and dynamic stiffness (Kdyn) were recorded using an acoustic crack detection device. Intact eggs were marked and replaced in the front of the cages. These eggs were subsequently passed through online collection, grading and packing machinery, along with a volume of unmarked eggs. At the end of packing the acoustic test was repeated on the marked eggs, and these were subsequently categorised as being either intact (0) or cracked (1). A logistic regression of the probability of cracking vs Kdyn revealed that as the Kdyn measurement decreases below 15 000N/m there is a rapid increase in the probability that an egg will crack during routine handling. Additional variables (visit, egg weight,% damping and position in the house (battery [1 to 7], side [1, 2] and tier [1 to 8]) were also fitted to the model but only egg weight, visit and tier effects significantly improved the model fit. This study confirms that the dynamic stiffness measurement can predict the probability of an egg cracking in the field and with high precision. As this measurement also has a high heritability, it could be incorporated into breeding programmes, where it would offer an excellent method to improve eggshell quality and reduce the incidence of cracked eggs.