In this paper we show that texture analysis of femoral neck trabecular patterns can be used to predict osteoporotic fractures. The study is based on a sample of 123 women aged 44-66 years with and without fractures. We analyzed trabecular patterns using the Co-occurrence Matrix texture analysis algorithm and compared the predictive utility of the textural data with densitometry. Logistic regression was used to estimate the predictive utility, exp(B), of clinical and textural data per standard deviation. Reproducibility was also demonstrated using paired films at 1-year intervals (CoV=4.5%). Bone mass estimated by DEXA measurements of the spine and hip were the most predictive of fractures giving a two-fold increase in fractures per s.d. bone mass loss (95% CI: 1.2-3.1, p<0.005). Age was also highly predictive with fracture risk increasing by 1.07-fold per year (95% CI: 1.01-1.14, p<0.02). Trabecular texture was found to give a lower, but significant, prediction of fracture of 1.5-fold per s.d. trabecular pattern loss (95% CI: 0.96-2.31, p<0.05). Combining age, weight, and trabecular texture increased the fracture prediction to 1.78-fold per s.d. (95% CI: 1.19-2.67). Combining trabecular texture with densitometry increased the predictive ability to 2.06-fold per s.d. (95% CI: 1.32-3.22) and combined with age and weight as well increased exp(B) to 2.1-fold per s.d. (95% CI: 1.32-3.35). This shows that osteoporotic trabecular texture changes can be "measured." Moreover, the combination of age, weight, and trabecular texture is more predictive than either alone. We propose therefore that this trabecular texture analysis is both reproducible and clinically meaningful. The application of such methods could be used to improve the estimation of fracture risk in conjunction with other clinical data, or where densitometry data cannot be obtained (e.g., in retrospective studies).