Three-dimensional (3D)-CT data is currently insufficient for classifying femoral trochanter fractures. Fracture classification based on fracture stability analysis is helpful to evaluate the prognosis of patients after internal fixation. Currently, there is a lack of fracture classification methods based on 3D-CT images and fracture stability analysis. The aim of this study was to propose a new six-part classification method for intertrochanteric fractures of femur based on 3D-CT images and fracture stability analysis to improve the diagnosis rate of unstable fractures. From January 2009 to December 2019, 320 patients receiving intramedullary nail surgery for femoral intertrochanteric fractures at Chengdu University's Affiliated Hospital were studied retrospectively. AO and six-part classifications were undertaken according to the 3D-CT image data of the patients, and the stability rates of two classifications were compared. According to the six-part classification stability criteria, the patients were divided into a stable and an unstable fracture group. The perioperative and follow-up indicators of the two groups were statistically analyzed, and the six-part classification's inter-observer and internal reliability was examined. There were 107 men and 213 females women the 320 patients, with an average age of 79.32 ± 11.26 years and an osteoporosis rate of 55.63% (178/320). The fracture stability rate of 39.69% (127/320) was studied using a six-part classification method. The AO classification fracture stability rate was 42.50% (136/320), with no significant difference (χ2 = 0.523, p = 0.470 > 0.05). There is no statistically significant difference between the two classification techniques in the examination of fracture stability (McNemer difference test p = 0.306 > 0.05; Kappa consistency test p < 0.001). According to the six-part classification, fracture stability and instability group were divided into two groups. The following indicators were compared between the two groups: The surgery time (p = 0.280), fracture reduction quality (p = 0.062); function independent measurement (p = 0.075); timed up and go test (TUG) (p = 0.191), and Parker-Palmer score (p = 0.146). Were as compared according to the six-part classification of stable and unstable fracture groups. Perioperative blood loss (p < 0.001), the Harris score excellent and good rate (p = 0.043), fracture healing time (p < 0.001), and the entire weight-bearing duration (p = 0.002) were statistically significant. The difference in femoral head height (FHH) (p = 0.046), the change in femoral neck shaft angle (p = 0.003), the change in medial cephalic nail length (p = 0.033), and the change in tip-apex distance (TAD) (p = 0.002) were statistically significant compared to the relevant markers of imaging stability. Fracture stability had a substantial influence on Harris ratings at 3, 6, and 12 months following surgery, according to repeated measures analysis of variance (F(1,126) = 32.604, p < 0.001). The effect of time on the Harris score was similarly significant (F(1.893,238.508) = 202.771, p < 0.001). The observer intra-observer inter-group correlation coefficient (ICC) value was 0.941 > 0.75, the inter-observer ICC value was 0.921 > 0.75, and the intra-observer and inter-observer reliability were both good. The six-part classification of femoral intertrochanteric fractures based on 3D-CT images has broader guiding relevance for femoral intertrochanteric fracture stability analysis. Clinicians will find this classification simpler and more consistent than the AO classification.