Breast carcinoma is the world’s most prevalent type of cancer.The building of predictive cytotoxicity breast cancer models assists permanent synthetic activities and give critical information about structure-activity of novel structure design through a quantitative Structure-Activity Relationship (QSAR) modelling application. Quantitative Structure-Activity Relationships (QSAR) present a model that links pharmacological and biological activities to chemical structures and molecular docking research reveals the medication’s interaction with its targeted enzymes. This review is dedicated for the detailed study of models for designing highly effective breast anticancer MCF7 cells. The Per-ARNT-SIM transcription factor family includes the Aryl hydrocarbon Receptor (AhR), which is a member recognized as a viable novel aim for the cure of breast cancer. The development of a series of 2-phenylacrylonitriles that target AhR has showed enticing and discerning efficacy against malignancy cells while preserving healthy and non-cancerous cell lines. This study aims to use estimating techniques such molecular docking studies, Quantitative Structure-Activity Relationship (QSAR) and QSAR model parameters to more advanced design new effective molecules and analyse the pharmacokinetics “drug-likeliness” assets of the new compounds before they could progress to pre-clinical trial. These investigations also showed that derivatives of 2-(4-fluorophenyl) imidazole-5-one were more potent anti-cancer therapeutic candidates against the MCF-7 cell line. This exemplifies a remarkable medical breakthrough in the fight against breast cancer (MCF-7 cell line).