The current study analyzed trends and drivers that influence agricultural mechanization in Bihar state (one of the states selected to bring Green Revolution 2.0) of India. The interview schedule was administered to 800 respondents, selected proportionately from 4 agro-climatic zones to collect primary data. For the first time top 20 farm machinery used in Bihar is tried to be ranked. Data were analyzed by using a multinomial logit model which predicts the likelihood of choosing each alternative in a given set of options. The findings indicate that overall pseudo R2 value i.e. Nagelkerke 0.768 suggesting the chosen independent variables show the variation probabilities of 76.8%. Thus one unit increase in owned land of farmers increases the probability of the agricultural mechanization ascend towards low to moderate mechanization category by a factor of 2.303 times. However apathy from officials was negatively significant at a 1% level which indicated a unit increase in apathy from officials reduces the probability of agricultural mechanization falling in the moderate category by 10%. The model explains that Wald statistics were significant at 1% level for variables such as Owned land, Apathy, Land fragmentation and Beneficiary (Wald value 7.527 P=0.006, OR= 2.743, 99% CI 1.064 to 7.073) where the probability of farm mechanization ascend from low farm mechanization to moderate mechanization category. The study concludes that farmers who rent their machinery and were direct beneficiaries of Bihar Krishi Roadmap for which Rs. 117074.30 Lakh was under subsidy for agricultural machinery, were having a higher propensity towards mechanization.