Failure to prioritize road maintenance can result in substantial economic losses and impede a country's development. Accordingly, timely maintenance is required, and it is crucial to establish maintenance criteria that prioritize areas in the worst condition. This involves developing a ranking procedure to optimize the use of limited funds. The objective of this study was to develop a model to prioritize gravel road maintenance in ARRCA's using the Analytic Hierarchy Process (AHP). AHP is the most suitable choice for prioritizing pavement sections for maintenance at the network level. Different selection criteria were established based on criteria from ERA's low volume road booklet G and various literatures. Eight criteria were identified through preliminary questionnaire surveys and interviews with professionals in the field and validated through statistical techniques using SPSS. The identified factors included: AADT, Connectivity of the road network (strategic inter-community or main road links), Social Services (serving markets, education, and health facilities), Population Served, Percentage of Vehicle Composition, Volume to Capacity Ratio, and Road Condition Survey. A main questionnaire survey using the AHP method and Saaty scales was conducted with experts and experienced professionals on gravel road maintenance and other highway engineers to weigh these factors. The weights were calculated using Expert Choice Software Version 11, and the following results were calculated: Volume to Capacity Ratio (30.9%), Percentage of Vehicle Composition (20.8%), AADT (16.9%), Population served (10.6%), and Road Condition Survey (8.4%) of a road link play the most significant role by taking the highest share. Next, a sample of 12 selected rural roads from ARRCA's under Debre Markos Rural Road Maintenance Office and Gondar RRM Office were considered. A complex matrix was developed to evaluate the priority score for gravel road periodic maintenance and determine which road links should be addressed first based on the aforementioned criteria. The results showed that RR5, a road from Merawi-Dejen terara-Birakat , attained the highest prioritization with an RRMPS score of 3.22 On the other hand, rural road (RR11), a road from Hamusit to Korata, received the lowest priority for maintenance with an RRMPS score of 1.442. A comparison was made between the maintenance project priority rank established by ARRCA and the priority rank determined using the model in this research. The results revealed a significant difference in the ranks of alternatives. Keywords: Gravel Road, SPSS, Analytic Hierarchy Process (AHP) and Prioritization.