Pediatric acute lymphoblastic leukemia (ALL) is a highly heterogeneous disease at the molecular level, with over 20 subtypes of B-cell ALL (B-ALL) identified to date. These subtypes are critical for guiding risk-adapted therapy and precision medicine, as they are defined by specific chromosomal rearrangements, gene expression profiles, aneuploidies and point mutations. However, the ability to accurately classify these subtypes is limited by the technical and economic challenges faced by many centers, particularly in low- and middle-income countries. In this study, we employed transcriptome sequencing to perform molecular classification of B-ALL at diagnosis in pediatric patients enrolled in the multicentric ALLIC-GATLA-2010 clinical protocol in Argentina. Using a combination of bioinformatic tools, we successfully identified single nucleotide variants, fusion transcripts and gene expression profiles, achieving molecular classification in over 90% of patients. Our analysis also revealed high-risk molecular features and novel genetic alterations. These findings hold potential clinical value for improving risk stratification and identifying therapeutic targets, particularly for patients who remain unclassified by conventional diagnostic methods.