Form factor functions are important to predict tree stem volumes at any height. These functions provide information about the volume of wood at a given diameter and height of the tree stem. The aim of this study was to develop form factor functions for Eucalyptus camaldulensis at Sirinka, North Wollo Zone of Amhara Regional State, Ethiopia. The sample trees were selected and categorized into five diameter classes, namely: 15-20 cm, 20-25 cm, 25-30 cm, 30-35 cm, and >35 cm. In each diameter class, 7-8 trees were sampled and measured. A total of 36 trees were taken for all diameter classes in the plantation of Eucalyptus camaldulensis. The sample tree selection was carried out purposively targeting the diameter class. Trees with multi-stems, broken stems, or crooked boles were not included in the measurements. Diameter at breast height (DBH) was measured using a caliper, and total tree height and height to the live crown was measured using a measuring tape. On a stem, DBH and height measurements were taken every 2 m interval. Five models, namely: Pollanschütz’s, Evert’s (Australian), Swedish’s, Meyer’s and Rosset’s were used to estimate the form factor (constant). The models were fit to express volume outside bark as functions of diameter outside bark and height. The models used nonlinear regression equations. Comparison of models was used using different coefficients such as coefficient of determination (R2), root mean square error (RMSE) and coefficient of variation (CV). The result suggests that pollanschutz’s form factor function for its higher R2 (33.4 %) and lower root mean square error (0.037) was the best in predicting coefficients at 5% probability for Eucalyptus camaldulensis at eastern Amhara region. This gave form factor (FF) value of 0.4664 with lower CV and higher R2. The result suggests that FF can be used for eucalyptus growing regions in order to estimate the growing stock and the volume of wood to be produced in the plantation. The FF supports the forest owners to pay reasonable tax for the government.