Subclinical mastitis (SCM) remains a widespread yet underdiagnosed issue in dairy herds, causing significant economic losses, particularly in low-resource environments with limited early detection tools. Somatic cell count (SCC) is a well-established and cost-effective method for detecting SCM in dairy production systems. This study aimed to estimate the prevalence of SCM and identify associated cow-level risk factors using on-farm SCC screening in a high-producing commercial dairy herd in Bangladesh. A cross-sectional survey was conducted in January 2025, involving 227 lactating cows. Milk samples were analyzed using the Ekomilk Horizon Analyzer (Bulteh 2000 Ltd., Bulgaria). SCM was defined as SCC ≥200,000 cells/mL, a threshold commonly applied in both industry and research. Cow-level data—including breed, body condition score (BCS), age, pregnancy status, reproductive disorders, abortion history, retained placenta, number of calves, lactation stage, and milk yield—were recorded. Univariable and multivariable logistic regression analyses identified factors associated with elevated SCC. The overall SCM prevalence was 63.4%. Multivariable analysis showed significant associations between reproductive disorders and SCM. Anestrus cows had 2.68 times higher odds (95% CI: 1.20–5.95; P = 0.015), and repeat breeders had 3.85 times higher odds (95% CI: 1.69–8.76; P < 0.001), compared to cows without reproductive issues. Additionally, cows weighing ≥345 kg had a 3.26-fold higher risk (95% CI: 1.77–5.99; P < 0.001). This pilot study confirms the feasibility of on-farm SCC screening for early SCM detection and identifies reproductive disorders and higher body weight as significant risk factors. These findings highlight the need for comprehensive herd health monitoring and targeted interventions. Larger-scale studies are essential to validate these results and inform effective management strategies aimed at improving dairy herd productivity and animal welfare in resource-constrained systems.