In the present study, we sought to determine the predictive value of selective nuclear morphometry (SNM) for patient outcome in renal cell carcinoma (RCC). Tumor samples of 140 renal adenocarcinomas diagnosed and treated with radical nephrectomy and hilar lymphadenectomy between 1970 and 1988 with a minimum follow up of 5 years in all the cases were studied by SNM. The morphometric analysis was performed in the most malignant tumor selected zone. Selection was based on cytological criteria including nuclear grade. Nuclear morphometric features analyzed were: area, perimeter, major diameter, major and minor diameter of the equivalent ellipse, volume of the equivalent ellipse and sphere, circumference diameter, and shape factors. The results showed that in the selected zone tumor nuclei were larger than in the zones selected at random. There was an inverse correlation between morphometric parameters and survival and a direct one between tumoral grade and stage. Tumors of the long-term survival group of patients presented nuclei with smaller morphometric measurements than tumors of short term survival group, with significant differences between them (p < 0.05). In the survival analysis carried out by the Kaplan-Meier method significant differences existed between different groups formed from break point for: area, perimeter, major diameter, major and minor diameter of the ellipse, volume of the ellipse and sphere, circumference diameter and perimeter shape factor. In the multivariate analysis carried out by the Cox method, the feature with the most predictable value related to survival, was the tumor stage. Morphometric value with the highest punctuation in the test was major nuclear diameter. The rest of the morphometric values (except elliptic shape factor and elongation factor) were also significant but they did not improve prognostic information of the major nuclear diameter. SNM offers a useful aid in a more objective grading of RCC. Multivariate Cox analysis revealed additional value of karyometry to tumor stage. SNM can be a useful tool for stratification of patients with RCC.