Background High-quality data are fundamental for effective monitoring of newborn morbidity and mortality, particularly in high burden lowand middle-income countries (LMIC). Methods We conducted a systematic review on the quality of routine health facility data used for newborn indicators in LMIC, including measures employed. Five databases were searched from inception to February 2021 for relevant observational studies (excluding case-control studies, case series, and case reports) and baseline or control group data from interventional studies, with no language limits. An adapted version (19-point scale) of the Critical Appraisal Tool to assess the Quality of Cross-Sectional Studies (AXIS) was used to assess methodological quality, and results were synthesized using descriptive analysis. Results From the 19572 records retrieved, 34 studies in 16 LMIC countries were included. Methodological quality was high (>14/19) in 32 studies and moderate (10-14/19) in two. Studies were mostly from African (n = 30, 88.2%) and South-East Asian (n = 24, 70.6%) World Health Organization (WHO) regions, with very few from Eastern Mediterranean (n = 2, 5.9%) and Western Pacific (n = 1, 2.9%) ones. We found that only data elements used to calculate neonatal indicators had been assessed, not the indicators themselves. 41 data elements were assessed, most frequently birth outcome. 20 measures of data quality were used, most along three dimensions: 1) completeness and timeliness, 2) internal consistency, and 3) external consistency. Data completeness was very heterogeneous across 26 studies, ranging from 0%-100% in routine facility registers, 0%-100% in patient case notes, and 20%-68% in aggregate reports. One study reported on the timeliness of aggregate reports. Internal consistency ranged from 0% to 96.2% in four studies. External consistency (21 studies) varied widely in measurement and findings, with specificity (6.4%-100%), sensitivity (23.6%-97.6%), and percent agreement (24.6%-99.4%) most frequently reported.