Recently, rateless codes have introduced a promising approach to obtaining wireless throughput higher than what is achieved by fixed-rate codes, especially over time-varying channels. Rateless codes like Raptor, Strider, and spinal codes naturally process all the information available at the receiver corresponding to a packet, whether from one or many frame transmissions. However, a profitable deployment of rateless codes in a wireless network requires a link-layer protocol to coordinate between sender and receiver. This protocol needs to determine how much coded data should be sent before the sender pauses for feedback from the receiver. Without such feedback, an open-loop sender would not know when the packet has been decoded, but sending this feedback is not free and consumes a significant fraction of the packet transmission time. This paper develops RateMore, a protocol that learns the probability distribution of the number of symbols required to decode a packet (the decoding CDF), and uses the learned distribution in a dynamic programming strategy to produce an optimal transmission schedule. Our experiments show that RateMore reduces overhead by between 2.6x and 3.9x compared to 802.11-style ARQ and between 2.8x and 5.4x compared to 3GPP-style “Try-after-n” HARQ.