The cost of repairing and maintaining a power tiller in Bangladesh is estimated using American standards which is not suitable with as the soil condition of Bangladesh. Hence, the specific objective of this study was to determine the actual unit factor for the repair and maintenance cost of power tiller used in Bangladesh. A structured questionnaire was prepared through active consultation with subject matter specialists. Data was collected from the 154 key informants who were involved in operating and maintaining the power tiller for at least 5 years. The study was conducted in Dinajpur, Bogura, Sirajganj, Sherpur, Jamalpur, Mymensingh, Tangail, Jashore, Narail, Khulna, and Sathkira districts of Bangladesh from 4 September 2020 to 17 September 2021. The key informants were identified using the Snowball Sampling Technique. Data such as purchase price of power tiller, the average working hour in a day and the total number of working days in a year, and repair and maintenance cost of power tiller for consecutive five years were collected in this study. A new power tiller provides service for the first one year without any major repairing. But after that time, the power tiller needs to be repaired 2-3 times a year. The percentage cost factor of the power tiller was found at 0.00223, 0.0041, 0.00563, 0.00706, and 0.00877 respectively, based on the repair and maintenance data of the power tiller for the consecutive five years. The average percentage cost factor of the power tiller varied within the range of 0.00486 to 0.00905. The average unit factor of repair and maintenance cost of power tiller was found 0.00651 in the Bangladesh context and analysis by Mean, square-R in the regression model. The regression equation for the R&M cost factor of power tiller concerning annual use was Y (hr./yr.) = 1478 + 112963 X; where X: Accumulated cost factor in % and Y: Accumulated annual use hr./yr.p-value is less than 0.00001 and variation of the data value was significant. This cost factor data needs to be introduced to the researchers and academicians for further use instead of using cost factors based on foreign data.