Haplotype‐based noninvasive prenatal diagnosis (NIPD) is applicable for various recessive single‐gene disorders in proband families. However, a comprehensive exploration of critical factors influencing the assay performance, such as fetal fraction, informative single nucleotide polymorphism (SNP) count, and recombination events, has yet to be performed. It is critical to identify key factors affecting NIPD performance, including its accuracy and success rate, and their impact on clinical diagnostics to guide clinical practice. We conducted a prospective study, recruiting 219 proband families with singleton pregnancies at risk for eight recessive single‐gene disorders (Duchenne muscular dystrophy, spinal muscular atrophy, phenylketonuria, methylmalonic acidemia, hemophilia A, hemophilia B, non‐syndromic hearing loss, and congenital adrenal hyperplasia) at 7–14 weeks of gestation. Haplotype‐based NIPD was performed by evaluating the relative haplotype dosage (RHDO) in maternal circulation, and the results were validated via invasive prenatal diagnosis or newborn follow‐ups. Among the 219 families, the median gestational age at first blood draw was 8+5 weeks. Initial testing succeeded for 190 families and failed for 29 due to low fetal fraction (16), insufficient informative SNPs (9), and homologous recombination near pathogenic variation (4). Among low fetal fraction families, successful testing was achieved for 11 cases after a redraw, while 5 remained inconclusive. Test failures linked to insufficient informative SNPs correlated with linkage disequilibrium near the genes, with F8 and MMUT exhibiting the highest associated failure rates (14.3% and 25%, respectively). Homologous recombination was relatively frequent around the DMD and SMN1 genes (8.8% and 4.8%, respectively) but led to detection failure in only 44.4% (4/9) of such cases. All NIPD results from the 201 successful families were consistent with invasive diagnostic findings or newborn follow‐up. Fetal fraction, informative SNPs count, and homologous recombination are pivotal to NIPD performance. Redrawing blood effectively improves the success rate for low fetal fraction samples. However, informative SNPs count and homologous recombination rates vary significantly across genes, necessitating careful consideration in clinical practice. We have designed an in silico method based on linkage disequilibrium data to predict the number of informative SNPs. This can identify genomic regions where there might be an insufficient number of SNPs, thereby guiding panel design. With these factors properly accounted for, NIPD is highly accurate and reliable.