Artificial intelligence, where machine learning is used, maybe a crucial tool for amending plant tissue culture. This method might potentially be used at different callus culture stages to research how quickly callus propagation occurs when it is exposed to various levels of plant growth hormone. Plant tissue culture is a field that enables culturing of various plants and parts of plants usually treated under a nutrient medium and in highly sterile conditions. Out of them callus culture is one of the very interesting arenas of plant biotechnology that encompasses many pivotal benefits. The study focuses on such callus enrichment using different hormones that thereby enhance its biological activities. The plant namely Ruta chalepensis was chosen upon wherein the callus growth was noticed. Ruta chalepensis has multiple medicinal activities like anti-cancer, anti-ulcer, anti-diabetic, and many more pharmacological properties that yield in treating and curing illness. The plant was examined characterized by MS medium and other hormones and its concentrations. auxin and cytokinin from 0.5mg to 2 mg( 2,4-D, NAA, BAP, IAA). Increased concentration of 2,4-D (1.0 mg/L) alone in the MS medium showed profuse callus growth. Among the plant growth regulators that were studied separately, 2,4-D (1.0 mg/L) followed by NAA (0.5 mg/L) showed maximum callus initiation, hence further work was carried out in a combination of with the plant growth regulators for callus proliferation and accumulation to study the growth the pattern on a combination of hormones and fix the hormone concentrations for the mass propagation of callus from the explants and was noticed that 2,4-D (1.0 mg/L) + NAA (0.5 mg/L) showed profuse callus growth in comparison with the other hormonal concentrations treated which is (0.5 mg/L) until (2.0 mg/L). The hormone combinations were hence used to train multiple machine learning models. The models used in this analysis are Random Forest regressor, decision tree regressor, multilayer perceptron, and support vector regressor and the aim was to identify the model best suited for predicting callus formation using the hormonal combinations at various concentrations.