Zero-inflated models is a class of statistical models specifically designed for the analysis of count data characterized by an excessive number of zero observations relative to standard distributions like the Poisson or Negative Binomial. This methodological approach accounts for zeros arising from two distinct processes, providing a more accurate representation and analysis of such data structures.