High resolution melting curve (HRM) is a recent advance for the detection of SNPs. The technique measures temperature induced strand separation of short PCR amplicons, and is able to detect variation as small as one base difference between samples. It has been applied to the analysis and scan of mutations in the genes causing human diseases. In plant species, the use of this approach is limited. We applied HRM analysis to almond SNP discovery and genotyping based on the predicted SNP information derived from the almond and peach EST database. Putative SNPs were screened from almond and peach EST contigs by HRM analysis against 25 almond cultivars. All 4 classes of SNPs, INDELs and microsatellites were discriminated, and the HRM profiles of 17 amplicons were established. The PCR amplicons containing single, double and multiple SNPs produced distinctive HRM profiles. Additionally, different genotypes of INDEL and microsatellite variations were also characterised by HRM analysis. By sequencing the PCR products, 100 SNPs were validated/revealed in the HRM amplicons and their flanking regions. The results showed that the average frequency of SNPs was 1:114 bp in the genic regions, and transition to transversion ratio was 1.16:1. Rare allele frequencies of the SNPs varied from 0.02 to 0.5, and the polymorphic information contents of the SNPs were from 0.04 to 0.53 at an average of 0.31. HRM has been demonstrated to be a fast, low cost, and efficient approach for SNP discovery and genotyping, in particular, for species without much genomic information such as almond.