Oppositional　defiant　symptoms　are　some　of　the　most　common　developmental　symptoms　in　children　and　adolescents　with　and　without　oppositional　defiant　disorder.　Research　has　addressed　the　close　association　of　the　parent-child　relationship　(PCR)　with　oppositional　defiant　symptoms.　However,　it　is　necessary　to　further　investigate　the　underlying　mechanism　for　forming　targeted　intervention　strategies.　By　using　a　machine　learning-based　causal　forest　(CF)　model,　we　investigated　the　heterogeneous　causal　effects　of　the　PCR　on　oppositional　defiant　symptoms　in　children　in　Chinese　elementary　schools.　Based　on　the　PCR　improvement　in　two　consecutive　years,　423　children　were　divided　into　improved　and　control　groups.　The　assessment　of　oppositional　defiant　symptoms　(AODS)　in　the　second　year　was　set　as　the　dependent　variable.　Additionally,　several　factors　based　on　the　multilevel　family　model　and　the　baseline　AODS　in　the　first　year　were　included　as　covariates.　Consistent　with　expectations,　the　CF　model　showed　a　significant　causal　effect　between　the　PCR　and　oppositional　defiant　symptoms　in　the　samples.　Moreover,　the　causality　exhibited　heterogeneity.　The　causal　effect　was　greater　in　those　children　with　higher　baseline　AODS,　a　worse　family　atmosphere,　and　lower　emotion　regulation　abilities　in　themselves　or　their　parents.　Conversely,　the　parenting　style　played　a　positive　role　in　causality.　These　findings　enhance　our　understanding　of　how　the　PCR　contributes　to　the　development　of　oppositional　defiant　symptoms　conditioned　by　factors　from　a　multilevel　family　system.　The　heterogeneous　causality　in　the　observation　data,　established　using　the　machine　learning　approach,　could　be　helpful　in　forming　personalized　family-oriented　intervention　strategies　for　children　with　oppositional　defiant　symptoms.