This paper deals with describing several influential factors that have significant impact on final fattening weight (FFW) as an output variable at domestic beef cattle enterprises from the Eastern part of Turkey. Multivariate adaptive regression splines (MARS) as a non-parametric analysis technique was preferred in the description of the influential factors and their interaction effects for each gender. Some probable factors such as age, province, education level, experience, social security, lands, and the reason at performing animal production were recorded on breeders. Also, first fattening weight and fattening period of the beef cattle were recorded. It was determined that predictive models based upon MARS algorithm explained virtually all of variability in the final fattening weight (FFW) for each gender when model assessment criteria (viz. R2, SDRATIO, GCV and Pearson correlation coefficient between real and estimated scores in the final fattening weight) in the current study were considered. SDRATIO estimates of the MARS models for male and female domestic beef cattle were close to 0.05. The estimated FFW scores were correlated almost at the highest level with the observed FFW scores for each gender (r~1.000, P<2.2 e-16). The R2 estimates were also the closest to unity for each gender. The results showed that MARS is a recommendable model in description of influential factors for subsequent comparable studies.