DNA methylation profiling by Illumina methylation array-based methods has revolutionized the molecular classification and diagnosis of brain tumors. A significant barrier to adopting these methods in a clinical environment is the requirement for specialized scanners, which results in high additional costs and a larger laboratory footprint. DNA sequencing-based alternatives are attractive because most clinical molecular pathology laboratories already use sequencers for other molecular assays. This study aimed to compare the utility of the newly developed sequencing-based enzymatic methyl sequencing (EM-seq) method paired with the Twist Human Methylome panel for brain tumor classification with standard Infinium Methylation BeadChip-based methods. We used DNA from fresh-frozen or formalin-fixed, paraffin-embedded (FFPE) brain cancer samples from 19 patients and 1 control sample to construct DNA libraries covering 3.98 million CpG sites. We developed and validated a bioinformatics pipeline to analyze target-enriched EM-seq (TEEM-seq) data in comparison with standard array-based methods for tumor classification and copy number profiling. We found high concordance between TEEM-seq and traditional methods, with high correlation coefficients (>0.98) between FFPE replicates. We successfully classified tumor samples into the expected molecular classes with robust prediction scores (>0.82). We observed that FFPE samples required a sequencing depth of at least 35x to achieve consistently high and reliable prediction scores. The TEEM-seq method has the potential to complement existing tumor classification methods and lower the barriers for the adoption of methylation profiling in routine clinical use.