Amphibians serve as vital indicators in ecotoxicity assessments, reflecting ecosystem health in both aquatic and terrestrial realms. Tadpoles, the early developmental stage of frogs, inhabit environments exposed to diverse harmful organic compounds from industrial and runoff sources. Examining each compound individually proves challenging, prompting the utilization of in-silico methods such as Quantitative Structure Toxicity Relationship (QSTR) and Quantitative Read-Across Structure Activity Relationship (q-RASAR). Leveraging the extensive US EPA’s ECOTOX database, encompassing acute LC50 toxicity and chronic endpoints, we extracted essential data including study types, exposure routes, and chemical categories. From this dataset, regression-based QSTR and q-RASAR models were developed, focusing on key chemical descriptors. The descriptors, encompassing features such as lipophilicity and unsaturation, were crucial for predicting acute toxicity, whereas the electrophilicity, nucleophilicity, and branching of the molecules played a pivotal role in chronic toxicity predictions. Subsequently, q-RASAR models, integrated with the" intelligent consensus" algorithm, were implemented to enhance predictive accuracy. Their performance was rigorously compared across various approaches. These refined models not only predict the toxicity of untested compounds but also unveil underlying structural influences. Validation through comparison with existing literature affirmed the relevance and robustness of our approach in the field of ecotoxicology.