During December 2019, a novel coronavirus named as 2019-nCoV, has emerged in Wuhan, China. The human to human transmission of this virus has also been established. Untill now the virus has infected more than seven thousand people and has spread to fifteen countries. The World Health Organization (WHO) has declared 2019-nCoV as global health emergency due to its outburst well beyond China. There is need to develop some vaccines or therapeutics to control or prevent 2019-nCoV infections. The bottleneck with current conventional approaches is that these require longer time for vaccine development. However, computer assisted approaches help us to produce effective vaccine in short time compared with conventional methods. In this study, bioinformatics analysis was used to predict B cell and T cell epitopes of surface glycoprotein of 2019-nCoV that could be suitable to trigger significant immune response. The sequence of surface glycoprotein was collected from the database and analyzed to identify the immunogenic epitope. Both B cell and T cell epitopes were analyzed so the predicted epitopes can stimulate both cellular and humoral immune responses. We predicted 13 B cell and 05 T cell epitopes that later on were joined with GPGPG linker to make a single peptide. This computational approach to design a multi epitope peptide vaccine against emerging 2019-nCoV allows us to find novel immunogenic epitopes against the antigen targets of surface 2019-nCoV surface glycoprotein. This multi epitope peptide vaccine may prove effective to combat 2019-nCoV infections.