The influence of the network structure on the emergence of collective dynamical behavior is an important topic of research that has not been fully understood yet. In the current work, it is shown how statistical regression analysis can be considered to address this issue. The regression model proposed suggests that the average shortest path length is the network property most influencing the degree of synchronization of Kuramoto oscillators. Moreover, this model revealed to be very accurate, being the predicted and measured values of synchronization highly correlated. Therefore, the regression modeling allows predicting the values of the dynamic variable in terms of network structure.