plaNETic uses a Bayesian neural network-based to model small (masses between 0.5 and 15 M_earth) exoplanets. The code efficiently computes posteriors of a planet's internal structure based on its observed planetary and stellar parameters. It uses a full grid accept-reject sampling algorithm. plaNETic also allows for different choices in priors concerning the expected abundance of water (formation inside vs. outside of iceline) and the planetary Si/Mg/Fe ratios (stellar vs. iron-enriched vs. free).