A non-parametric, linear programming method for assessing the relative effectiveness of the homogeneous decision maker units (DMUs) is data envelopment analysis . The agricultural performance of the Indian State and UT is discussed in this article. Here, the output parameters include production of rice, oil-seeds, sugarcane, pulses, wheat , and coarse cereals, whereas input parameters are yearly rainfall, GDP, the number of employees, population, and net cultivated area. To evaluate the agricultural productivity of India’s states and union territories using the CCR, Input Oriented BCC, and Output Oriented BCC models.The efficacy scores of several models are compared and the super efficiency model is used to rank all of India’s states and UTs. Results: According to CCR model results, 74.19% of Indian states and UTs are efficient, whereas BCC models show 77.42% States and UTs are efficient. The most efficient unit is Madhya Pradesh, while the least inefficient unit is Kerala and the states ranked base on super efficiency score. Limitation: Changing the quantity of inputs and outputs has an impact on the agricultural performance of the Indian States and UTs. Other environmental and social parameters can be used to assess agricultural sustainability. Comparison of qualitative variables is not allowed in the traditional DEA model.