This study examined the determinants of wealth index among online shoppers using an ordinal logistic regression (OLR) framework. Data were collected through an online survey measuring demographic characteristics, behavioral attributes, and influencing factors for online shopping, with responses assessed using Likert-scale items. The sample (N = 86) consisted predominantly of respondents aged below 25 years (36.0%) and male (66.3%), with 41.9% employed, 36.0% students, and 22.1% self-employed. Wealth index distribution indicated that 47.6% fell into the low category, 32.1% medium, and 20.2% high. Factor analysis revealed three principal dimensions influencing online shopping behavior: decision-influencing factors, attitude factors, and motivation factors. The OLR model significantly improved prediction over the intercept-only model, χ²(11) = 39.64, p < .001, with acceptable fit (Pearson χ²(95) = 90.92, p = .599; Deviance χ²(95) = 69.79, p = .976) and moderate explanatory power (Nagelkerke R² = .599). Age and employment status emerged as the only significant predictors: respondents under 45 years and students were substantially less likely to belong to higher wealth index categories compared to older and employed individuals. Other behavioral and attitudinal variables did not show significant effects. The findings highlight the dominance of demographic factors over behavioral traits in determining online shoppers’ wealth capacity, offering valuable insights for e-commerce market segmentation and targeted marketing strategies.