Background: Pneumonia is one of the most important causes of morbidity and mortality in children. Identification and characterization of pathogens that cause infections are crucial for accurate treatment and accelerated recovery of the patients. However, in most cases the causative agent cannot be identified partly due to the limited spectrum covered by current diagnostics based on nucleic acid amplification. Therefore, in this study we explored the application of metagenomic next-generation sequencing (mNGS) for the diagnosis of children with severe pneumonia. Methods: From April to July 2017, 32 children were hospitalized with severe pneumonia in Shenzhen Children’s Hospital. Blood tests were conducted immediately after hospitalization to assess infection, oropharygeal swabs were collected to identify common pathogens. After bronchoscopy, bronchoalveolar lavage fluids (BALFs) were collected for further pathogen identification using standardized laboratory and mNGS. Results: Blood tests were normal in 3 of the 32 children. In oropharygeal swabs from 5 patients Mycoplasma pneumoniae by qPCR, 27 cases showed negative results for common pathogens. In BALFs we detected 6 cases with Mycoplasma pneumoniae with qPCR, 9 patients with adenovirus by using a Direct Immunofluorescence Assay (DFA) and 4 patients with bacterial infections, as determined by culture, In 3 of the cases a co-infection was detected. In 15 cases no common pathogens were found in BALF samples, using the current diagnostics, while in all the 32 BALFS pathogens were identified using mNGS, including adenovirus, Mycoplasma pneumoniae, Streptococcus pneumoniae, Haemophilus influenzae, Moraxella catarrhalis, cytomegalovirus andbocavirus. Conclusions: mNGS can increase the sensitivity of detection of the causative pathogens in children with severe pneumonia. In addition, mNGS will give more strain specific information, will help to identify new pathogens and could potentially help to trace and control outbreaks. In this study we have shown that it is feasible to have the results within 24 hours, making the application of mNGS feasible for clinical diagnostics.