Predicting the peak ground velocity of vibrations is essential to blast mining operationsin order to design the charge weights so as not to exceed certain thresholds that pre-vent damage to buildings and other infrastructure. The problem is usually marred by alarge scatter of observed peak ground velocity due to unknown complexities of seismicwave propagation. Classic peak ground velocity prediction methods employ empiricalformulas, the most widespread being the scaled distance approach that has the leastparameters to calibrate and works for a single sensor. In this study, we used data from55 mining production blasts recorded by an array of 81 seismic sensors in an open pitiron ore mine in Austria. We evaluated and compared different methods for predictingpeak ground velocity. The large data set provides sufficient constraint to independentlyresolve the charge weight exponentc, the radial decay constantband local site factors.Thec/b-ratio of 0.2 that we find for our site is far smaller than that implied by the USBureau of Mining scaled distance method, and peak ground velocity predictions madewith the latter approach are significantly worse. This highlights the importance of usingsite-specific data to calibrate predictive models and suggests that relying on arbitrarypriors may lead to inaccurate predictions. For the charge weight exponent, we find avalue of 0.5 which we interpret as expression of the physical relationship among chargeweight, energy and amplitude, suggesting that this may be a global, site-independent,value. This result has probable a broader relevance beyond our specific location andcould improve prediction outcomes on other sites.