Farming risks play a great role with the fortune of Indian cultivators. But, Indian cultivators’ financial crisis starts mainly when they cultivate with the borrowed fund and after certain crop loss they fail to pay back that money. Crop insurance brings definitely a solution of this big problem to these poor farmers. A diagnostic approach towards finding out different farm risks and designing a perceptual map for positioning these farm risks on the basis of their level of severity are highlighted as the prerequisites for the adoption of any crop insurance programme. Primary survey data have been collected for this purpose with manual circulation of structured questionnaires since November 2020 to January 2021. A multistage random sampling has been employed to select two districts from each of the select five states of this country and from each district two blocks are selected at random. Total 20 blocks have been selected and 25 respondents are selected randomly from the villages of each block. Considering different earlier literatures in this context, farm risks are selected purposively to perform the multi-dimensional scaling (MDS), and these risks are those which are most frequently faced by the farmers of these select five states of India. Thus, the relative positions of the perceived farm risks are framed on the perceptual map. After considering the position of each perceived risk, an ordinary least square regression (OLS) is attempted to explore the effect of farm risks’ vulnerability as select multi-nominal variables on the adoptability of crop insurance as an outcome variable.