Summary: In general, standard binomial regression models do not fit well to proportion data from biological control assays, mainly when there is excess of zeros and overdispersion. In this study, beta-binomial and zero-inflated beta-binomial models are applied to a data set obtained from a biological control assay to produce parasitized eggs to control Diatraea saccharalis, a common pest in sugar cane. A parasite (Trichogramma galloi) was put to parasitize 128 eggs of Anagasta kuehniella, an economically suitable alternative host, with a variable number of female parasites (\(2, 4, 8,\dots, 128\)), each with 10 replicates in a completely randomized experiment. A Bayesian procedure was formulated using a simulation technique (Metropolis Hastings) for estimation of the parameters of interest. The convergence of the Markov chain generated was monitored by visualization of the trace plot and using Raftery & Lewis and Heidelberger & Welch diagnoses presented in module CODA of software R.