Background Cycling to school has large potential health benefits, ensuring children get regular daily exercise. This paper demonstrates and implements a method for estimating the potential for modal switch to cycling for the school commute down to the route network level across England. Methods Input data from the 2011 School Census, provided by the English Department for Education, comprised two main tables: a school-level dataset representing 21,523 educational institutions and an origin-destination (OD) level dataset, containing around 50 desire lines per school. The method focused on the 1.37 million secondary school children (age 11-18) travelling less than 15km to school. For each of the 134,274 OD pairs we route distance and hilliness were estimated using the CycleStreets.net routing service. Current and potential levels of cycling were modeled as a function of distance and hilliness. This included using Dutch National Travel Survey to create a ‘Go Dutch’ scenario English children cycled as much as children in the Netherlands, accounting for route distance and hilliness. Results Among those travelling less than 15km, the current percentage of children cycling to school in England is 2.7%. Our model of cycling potential highlights areas and routes with particularly high cycling potential, to help prioritize investment in safe routes to school. The scenarios show the scale of transformation possible in school travel patterns: ‘Going Dutch’ would see over two-thirds of these children cycle to school, approaching the level observed in The Netherlands, higher than the 27% cycle mode share in an equivalent ‘Go Dutch’ scenario for cycling to work, implying that the potential uptake of cycling for travel to school could be even higher, as a percentage of trips, than the potential for cycling to work. Conclusions This paper highlights the very high potential of school trips to be cycled and suggest it should be a priority target for health-conscious transport policy. To our knowledge, this is the first time that a national database on school travel at the level has been analysed from a ‘safe routes to school’ perspective at high geographical resolution, down to the route network level. The methods could be deployed in other settings where travel to school data is available at the OD level to inform investments in safe routes to school, where they are most needed.