Current in vitro models for hepatotoxicity commonly suffer from low detection rates due to incomplete coverage of bioactivity space. Additionally, in vivo exposure measures such as Cmax are used for hepatotoxicity screening which are unavailable early on. Here we propose a novel rule-based framework to extract interpretable and biologically meaningful multi-conditional associations to prioritize in vitro endpoints for hepatotoxicity and understand the associated physicochemical conditions. The data used in this study was derived for 673 compounds from 361 ToxCast bioactivity measurements and 29 calculated physicochemical properties against two lowest effective levels (LEL) of rodent hepatotoxicity from ToxRefDB, namely 15mg/kg/day and 500mg/kg/day. In order to achieve 80% coverage of toxic compounds, 35 rules with accuracies ranging from 96% to 73% using 39 unique ToxCast assays are needed at a threshold level of 500mg/kg/day, whereas to describe the same coverage at a threshold of 15mg/kg/day 20 rules with accuracies of between 98% and 81% were needed, comprising 24 unique assays. Despite the 33-fold difference in dose levels, we found relative consistency in the key mechanistic groups in rule clusters, namely i) activities against Cytochrome P, ii) immunological responses, and iii) nuclear receptor activities. Less specific effects, such as oxidative stress and cell cycle arrest, were used more by rules to describe toxicity at the level of 500mg/kg/day. Although the endocrine disruption through nuclear receptor activity formulated an essential cluster of rules, this bioactivity is not covered in four commercial assay setups for hepatotoxicity. Using an external set of 29 drugs with drug-induced liver injury (DILI) labels, we found that the likelihood of liver toxicity increases as compounds' promiscuity over important assays increases. In vitro-in vivo associations were also improved by incorporating physicochemical properties especially for the potent, 15mg/kg/day toxicity level, as well for assays describing nuclear receptor activity and phenotypic changes. The most frequently used physicochemical properties, predictive for hepatotoxicity in combination with