The warming of climate is a major setback to the farmers, and it leads to changes in cropping patterns in agriculture. To standardize the farm income the farmer has to avail the crop insurance. The Pradhan Mantri Fasal Bima Yojana helped to guard the farmers from crop loss due to unexpected movements alleviate the heavy weight of financial risk on farmers and stabilize their farm income. The beneficiaries of the sample of 120 farmers in the Srikakulam district of Andhra Pradesh. In Srikakulam ten farmers from each village were randomly selected namely Muddada, Ponnada, Ibrahimbad, Konagaram from Etcherla Mandal; Gara, Korlam, Korni, Kothurusyrigam from Gara Mandal; Telukunchi, Tulasigam, Paitharikeerthipuram, Haripuram from Ichchpuram mandal were selected for the study. Thus a total of twelve (12) villages were chosen for the study. The ex-post facto Research design was used for this study. Pearson’s Correlation Coefficient (r) and Multiple Linear Regression (MLR) are some statistical tools used in this study. Independent variables studied landholding, extension contact, disaster occurrence pattern, mass media utilization, training undergone, scientific orientation, risk orientation are positively and significantly correlated with the knowledge level of beneficiaries of PMFBY at a one per cent level of significance. Further, the correlation coefficient (r) values of material possession, and crop loan availed are positively and significantly correlated with the knowledge level of beneficiaries of PMFBY at a five per cent level of significance. The remaining independent variables education, farming experience, and annual income are positively and non-significant in their relationship with the knowledge about PMFBY. It observed that the ‘r’ values of land holdings, disaster occurrence pattern, extension contact, mass media utilization, training undergone, scientific orientation, risk orientation, and crop loan availed are positively and significantly correlated at one per cent level of significance with the opinion. The variables such as education, annual income, farming experience, and material possession are positively significantly correlated with the opinion.