The current spread of the SARS-CoV-2 coronavirus is a challenge for the entire world. Ivermectin is a promising agent, which could be used to combat the SARS-CoV-2 coronavirus. It represents a complex of semisynthetic derivatives of natural avermectins that have been taken advantage of for a long time in medicine and agriculture as antiparasitic drugs. However, the experimental ecotoxicology assessment data for individual avermectins are still scarce. In relation to this, the aim of this study is to develop a mathematical model that would allow reliably predicting the biotransformation ability of natural and semisynthetic avermectins and identifying the structural fragments of avermectin molecules that have the largest impact on this biological activity. The base for the model construction was a structurally heterogeneous set including organic compounds with experimentally determined biotransformation half-life periods (KmHL). Using the OCHEM web platform (https://ochem.eu) with the implemented PyDescriptor plugin for the descriptor calculation and Random Forest and Transformer-CNN algorithms, a satisfactory (R² _test= 0.81) Quantitative Relationship Structure—Activity (QSAR) model was developed. The subsequent calculations have shown that natural avermectins undergo on average faster biotransformation in fish than the semisynthetic ones. In addition, structural fragments that increase and decrease the biotransformation rate are identified.